Check results for 'grasp'

using R version 2.7.1 (2008-06-23)
using session charset: UTF-8

checking for file 'grasp/DESCRIPTION' ... OK

this is package 'grasp' version '2.5-4'

checking package dependencies ... OK

checking if this is a source package ... OK

checking whether package 'grasp' can be installed ... OK

checking package directory ... OK

checking for portable file names ... OK

checking for sufficient/correct file permissions ... OK

checking DESCRIPTION meta-information ... OK

checking top-level files ... OK

checking index information ... OK

checking package subdirectories ... OK

checking R files for non-ASCII characters ... OK

checking R files for syntax errors ... OK

checking whether the package can be loaded ... OK

checking whether the package can be loaded with stated dependencies ... OK

checking for unstated dependencies in R code ... OK

checking S3 generic/method consistency ... OK

checking replacement functions ... OK

checking foreign function calls ... OK

checking R code for possible problems ... NOTE
grasp: no visible binding for global variable ‘XXXpred’
grasp: no visible binding for global variable ‘YYY’
grasp: no visible binding for global variable ‘XXX’
grasp: no visible binding for global variable ‘OPTIONS’
grasp: no visible binding for global variable ‘gr.modmask’
grasp: no visible binding for global variable ‘DATAFILTER’
grasp: no visible binding for global variable ‘WEIGHTS’
grasp.adm.dump: no visible binding for global variable ‘OPTIONS’
grasp.exp.cormat: no visible binding for global variable ‘gr.selX’
grasp.exp.cormat: no visible binding for global variable ‘OPTIONS’
grasp.exp.cormat: no visible binding for global variable ‘YYY’
grasp.exp.cormat: no visible binding for global variable ‘gr.selXCOR’
grasp.exp.cormat: no visible binding for global variable ‘XXX’
grasp.exp.cormat: no visible binding for global variable ‘gr.modmask’
grasp.exp.cormat : panel: no visible binding for global variable ‘YYY’
grasp.exp.cormat : panel: no visible binding for global variable
‘OPTIONS’
grasp.exp.datamap: no visible binding for global variable ‘YYY’
grasp.exp.datamap: no visible binding for global variable ‘OPTIONS’
grasp.exp.datamap: no visible binding for global variable ‘XXX’
grasp.exp.datamap: no visible binding for global variable ‘gr.modmask’
grasp.exp.datamap: no visible binding for global variable ‘CONTOURS’
grasp.exp.distry: no visible binding for global variable ‘OPTIONS’
grasp.exp.distry: no visible binding for global variable ‘YYY’
grasp.exp.distry: no visible binding for global variable ‘gr.modmask’
grasp.exp.distry: no visible global function definition for ‘chisq.gof’
grasp.exp.histo: no visible binding for global variable ‘gr.selX’
grasp.exp.histo: no visible binding for global variable ‘OPTIONS’
grasp.exp.histo: no visible binding for global variable ‘YYY’
grasp.exp.histo: no visible binding for global variable ‘gr.modmask’
grasp.exp.histo: no visible binding for global variable ‘XXX’
grasp.exp.RvsP: no visible binding for global variable ‘gr.selX’
grasp.exp.RvsP: no visible binding for global variable ‘YYY’
grasp.exp.RvsP: no visible binding for global variable ‘OPTIONS’
grasp.exp.RvsP: no visible binding for global variable ‘XXX’
grasp.exp.RvsP: no visible binding for global variable ‘gr.modmask’
grasp.exp.RvsP: no visible binding for global variable ‘WEIGHTS’
grasp.exp.summary: no visible binding for global variable ‘YYY’
grasp.exp.summary: no visible binding for global variable ‘OPTIONS’
grasp.exp.summary: no visible binding for global variable ‘gr.modmask’
grasp.exp.summary: no visible binding for global variable ‘XXX’
grasp.exp.summary: no visible binding for global variable ‘gr.selX’
grasp.exp.xpredplot: no visible binding for global variable ‘XXX’
grasp.exp.xpredplot: no visible binding for global variable ‘OPTIONS’
grasp.exp.xpredplot: no visible binding for global variable ‘XXXpred’
grasp.in: no visible binding for global variable ‘YYY’
grasp.in: no visible binding for global variable ‘XXX’
grasp.in: no visible binding for global variable ‘XXXpred’
grasp.in: no visible binding for global variable ‘DROP.CONTRIB’
grasp.in: no visible binding for global variable ‘ALONE.CONTRIB’
grasp.in: no visible binding for global variable ‘MODEL.CONTRIB’
grasp.in: no visible binding for global variable ‘gr.lastcontrib1’
grasp.in: no visible binding for global variable ‘gr.lastcontrib2’
grasp.in: no visible binding for global variable ‘gr.lastcontrib3’
grasp.in: no visible binding for global variable ‘contribution1’
grasp.in: no visible binding for global variable ‘contribution2’
grasp.in: no visible binding for global variable ‘contribution3’
grasp.in: no visible binding for global variable ‘VALIDATION’
grasp.in: no visible binding for global variable ‘OPTIONS’
grasp.in: no visible binding for global variable ‘WEIGHTS’
grasp.int.contplot: no visible binding for global variable ‘YYY’
grasp.int.contplot: no visible binding for global variable ‘OPTIONS’
grasp.int.contplot: no visible binding for global variable ‘MODELCALLS’
grasp.int.contplot: no visible binding for global variable ‘XXX’
grasp.int.contplot: no visible binding for global variable
‘DROP.CONTRIB’
grasp.int.contplot: no visible binding for global variable
‘MODEL.CONTRIB’
grasp.int.contplot: no visible binding for global variable
‘ALONE.CONTRIB’
grasp.int.contrib: no visible binding for global variable ‘YYY’
grasp.int.contrib: no visible binding for global variable ‘OPTIONS’
grasp.int.contrib: no visible binding for global variable ‘MODELCALLS’
grasp.int.contrib: no visible binding for global variable
‘ALONE.CONTRIB’
grasp.int.contrib: no visible binding for global variable
‘DROP.CONTRIB’
grasp.int.contrib: no visible binding for global variable
‘MODEL.CONTRIB’
grasp.int.contrib: no visible binding for global variable ‘XXX’
grasp.int.plot: no visible binding for global variable ‘YYY’
grasp.int.plot: no visible binding for global variable ‘OPTIONS’
grasp.int.plot: no visible binding for global variable ‘MODELCALLS’
grasp.int.plot: no visible binding for global variable ‘XXX’
grasp.int.plot: no visible global function definition for ‘plot.gam’
grasp.int.response: no visible binding for global variable ‘OPTIONS’
grasp.int.response : grasp.pred.lookup2: no visible binding for global
variable ‘MODELCALLS’
grasp.int.response : grasp.pred.lookup2: no visible binding for global
variable ‘XXX’
grasp.int.response : grasp.pred.lookup2: no visible binding for global
variable ‘gr.selX’
grasp.int.response : grasp.pred.lookup2: no visible binding for global
variable ‘gr.modmask’
grasp.int.response: no visible binding for global variable ‘gr.selX’
grasp.int.response: no visible binding for global variable ‘XXX’
grasp.int.response: no visible binding for global variable ‘YYY’
grasp.int.response: no visible binding for global variable ‘MODELCALLS’
grasp.mod.anova: no visible binding for global variable ‘YYY’
grasp.mod.anova: no visible binding for global variable ‘OPTIONS’
grasp.mod.anova: no visible binding for global variable ‘MODELCALLS’
grasp.mod.anova: no visible binding for global variable ‘XXX’
grasp.mod.validate: no visible binding for global variable ‘YYY’
grasp.mod.validate: no visible binding for global variable ‘OPTIONS’
grasp.mod.validate: no visible binding for global variable ‘MODELCALLS’
grasp.mod.validate: no visible binding for global variable ‘XXX’
grasp.mod.validate: no visible binding for global variable ‘VALIDATION’
grasp.mod.validate: no visible binding for global variable ‘gr.modmask’
grasp.mod.validate: no visible binding for global variable ‘gr.EVA.ROC’
grasp.msk.limits: no visible binding for global variable ‘OPTIONS’
grasp.msk.limits: no visible binding for global variable ‘YYY’
grasp.msk.limits: no visible binding for global variable ‘gr.modmask’
grasp.msk.limits: no visible binding for global variable ‘gr.predmask’
grasp.msk.limits: no visible binding for global variable ‘XXX’
grasp.msk.limits: no visible binding for global variable ‘XXXpred’
grasp.options: no visible binding for global variable ‘gr.selX’
grasp.options: no visible binding for global variable ‘XXXpred’
grasp.options: no visible binding for global variable ‘XXX’
grasp.pred: no visible binding for global variable ‘YYY’
grasp.pred: no visible binding for global variable ‘OPTIONS’
grasp.pred: no visible binding for global variable ‘MODELCALLS’
grasp.pred: no visible binding for global variable ‘XXX’
grasp.pred: no visible binding for global variable ‘gr.predmat’
grasp.pred: no visible binding for global variable ‘XXXpred’
grasp.pred: no visible binding for global variable ‘gr.predmask’
grasp.pred.export: no visible binding for global variable ‘YYY’
grasp.pred.export: no visible binding for global variable ‘OPTIONS’
grasp.pred.export: no visible binding for global variable ‘MODELCALLS’
grasp.pred.export: no visible binding for global variable ‘XXXpred’
grasp.pred.export: no visible binding for global variable ‘gr.predmat’
grasp.pred.lookup: no visible binding for global variable ‘YYY’
grasp.pred.lookup: no visible binding for global variable ‘OPTIONS’
grasp.pred.lookup: no visible binding for global variable ‘MODELCALLS’
grasp.pred.lookup: no visible binding for global variable ‘XXX’
grasp.pred.lookup: no visible binding for global variable ‘wc’
grasp.pred.lookup: no visible binding for global variable ‘XXXlut’
grasp.pred.lookup: no visible binding for global variable ‘XXXpred’
grasp.pred.lookup: no visible binding for global variable ‘gr.modmask’
grasp.pred.lookup: no visible binding for global variable ‘gr.predmask’
grasp.pred.plot: no visible binding for global variable ‘YYY’
grasp.pred.plot: no visible binding for global variable ‘OPTIONS’
grasp.pred.plot: no visible binding for global variable ‘XXXpred’
grasp.pred.plot: no visible binding for global variable ‘gr.predmat’
grasp.step: no visible binding for global variable ‘YYY’
grasp.step: no visible binding for global variable ‘OPTIONS’
grasp.step: no visible binding for global variable ‘MODELCALLS’
grasp.step: no visible binding for global variable ‘gr.modmask’
grasp.step: no visible binding for global variable ‘XXX’
grasp.step: no visible binding for global variable ‘WEIGHTS’
grasp.step.anova: no visible binding for global variable ‘OPTIONS’
grasp.step.bruto: no visible binding for global variable ‘YYY’
grasp.step.bruto : bruto.gam: no visible binding for global variable
‘OPTIONS’
grasp.step.bruto : bruto.gam: no visible binding for global variable
‘XXX’
grasp.step.bruto : bruto.gam: no visible binding for global variable
‘YYY’
grasp.step.bruto : bruto.gam: no visible binding for global variable
‘gr.modmask’
grasp.step.bruto : bruto.gam: no visible binding for global variable
‘WEIGHTS’
grasp.step.bruto: no visible binding for global variable ‘MODELCALLS’
grasp.step.bruto: no visible binding for global variable ‘gr.modmask’
grasp.step.bruto : bruto.scope: no visible binding for global variable
‘XXX’
grasp.step.bruto: no visible binding for global variable ‘XXX’
grasp.step.bruto: no visible binding for global variable ‘OPTIONS’
grasp.step.contrib: no visible binding for global variable ‘XXX’
grasp.step.contrib: no visible binding for global variable ‘wc’
grasp.step.contrib: no visible binding for global variable ‘OPTIONS’
grasp.step.cross: no visible binding for global variable ‘gr.statname’
grasp.step.cross: no visible binding for global variable ‘gr.StatSel’
grasp.step.cross: no visible binding for global variable ‘gr.CrossSel’
grasp.step.cross: no visible binding for global variable
‘PLOTCROSS.VAL’
grasp.step.cross: no visible binding for global variable
‘PLOTCROSS.CVAL’
grasp.step.cross: no visible binding for global variable ‘gr.Yi’
grasp.step.crossplot: no visible binding for global variable ‘YYY’
grasp.step.crossplot: no visible binding for global variable ‘OPTIONS’
grasp.step.crossplot: no visible binding for global variable
‘PLOTCROSS.VAL’
grasp.step.crossplot: no visible binding for global variable
‘PLOTCROSS.CVAL’
grasp.step.crossval: no visible binding for global variable ‘YYY’
grasp.step.crossval: no visible binding for global variable ‘gr.Yi’
grasp.step.crossval: no visible binding for global variable ‘OPTIONS’
grasp.step.crossval: no visible binding for global variable ‘XXX’
grasp.step.crossval: no visible binding for global variable
‘gr.modmask’
grasp.step.full: no visible binding for global variable ‘YYY’
grasp.step.full: no visible binding for global variable ‘OPTIONS’
grasp.step.full: no visible binding for global variable ‘MODELCALLS’
grasp.step.full: no visible binding for global variable ‘gr.modmask’
grasp.step.full: no visible binding for global variable ‘XXX’
grasp.step.scope: no visible binding for global variable ‘XXX’
grasp.step.scope: no visible binding for global variable ‘OPTIONS’
grasp.step.start: no visible binding for global variable ‘OPTIONS’
grasp.step.start: no visible binding for global variable ‘gr.selXCOR’
grasp.step.start: no visible binding for global variable ‘gr.Yi’
grasp.step.start: no visible binding for global variable ‘XXX’
grasp.step.start: no visible binding for global variable ‘YYY’
Found possibly global 'T' or 'F' in the following function:
grasp.exp.distry

checking Rd files ... OK

checking Rd cross-references ... OK

checking for missing documentation entries ... OK

checking for code/documentation mismatches ... OK

checking Rd \usage sections ... OK

checking data for non-ASCII characters ... OK

creating grasp-Ex.R ... OK

checking examples ... ERROR
Running examples in 'grasp-Ex.R' failed.
The error most likely occurred in:

> ### * grasp
>
> flush(stderr()); flush(stdout())
>
> ### Name: grasp
> ### Title: Generalized Regression Analysis and Spatial Prediction
> ### Aliases: grasp
> ### Keywords: models
>
> ### ** Examples
>
>
> data(YYY) # reads in YYY,XXX and XXXpred demo dataset
> data(XXX)
> data(XXXpred)
> grasp.in(YYY,XXX,XXXpred) # initialize a new grasp session
#
# FUNCTION: grasp.in
# (by A. Lehmann )
# initializes the GRASP objects
#
creates YYY
creates gr.modmask
creates XXX
creates XXXpred
creates gr.predmat
creates gr.predmask
INFO: old contributions removed
#
# FUNCTION: grasp.options (by A. Lehmann)
# Sets the OPTIONS that are used by the different grasp functions
#
####################### GRASP OPTIONS ##########################

========== SET OPTIONS ===========
GRASP:
TITLE : GRASP:
PATH : c:/temp
PATHPNG : c:/temp
PATHLOG : c:/temp
PATHLUT : c:/temp
PLOTPAR : c(3, 3)
NBAR : 10
NPAST : 0
LIM : and
SELXLIM : 2
CORLIM : 1
RECALCULATEWEIGHTS : FALSE
CORTHIN : 1
CORPLOT : TRUE
DF1 : c(NA, NA, NA, NA, NA, NA, NA, NA, NA)
DF2 : c(4, 4, 4, 4, 4, 4, 4, 4, 4)
SMOOTHER : s
TEST : F
PERCONT : FALSE
DIRECTION : both
P.limit : 0.05
MINCONTRIB : 0
STARTWITH : 2
RESETSTART : TRUE
SHOWDETAIL : FALSE
CONTPLOT : histo
CVGROUPS : 5
RESOLUTION : 2500
STDERROR : TRUE
FAM : binomial

=========================================
INFO: old datafilter removed
**********************************************************************
********** REUSE GRASP.IN EACH TIME YOU MODIFY YOUR DATA *************
**********************************************************************
[1] "INPUT OK"
>
> grasp(2:3,c(4:6,8:9), title = "GRASP: ", path = "", gr.fam = "binomial", weights = TRUE, make.summary = TRUE, plot.maps = TRUE, plot.distry = TRUE, plot.histograms = TRUE, plot.respvspred = TRUE, plot.xpred = TRUE,plot.correlation = TRUE, stepwise.models = TRUE, test = "AIC", contributions = TRUE, plot.contributions = TRUE, plot.models = TRUE, model.anova = TRUE, validate.models = TRUE, predictions = TRUE, plot.predictions = TRUE)
#
# FUNCTION: grasp.options (by A. Lehmann)
# Sets the OPTIONS that are used by the different grasp functions
#
####################### GRASP OPTIONS ##########################

========== SET OPTIONS ===========
GRASP:
TITLE : GRASP:
PATH :
PATHPNG :
PATHLOG :
PATHLUT :
PLOTPAR : c(3, 3)
NBAR : 10
NPAST : 10
LIM : and
SELXLIM : c(4, 5, 6, 8, 9)
CORLIM : 1
RECALCULATEWEIGHTS : TRUE
CORTHIN : 1
CORPLOT : TRUE
DF1 : c(NA, NA, NA, NA, NA, NA, NA, NA, NA)
DF2 : c(4, 4, 4, 4, 4, 4, 4, 4, 4)
SMOOTHER : s
TEST : AIC
PERCONT : FALSE
DIRECTION : both
P.limit : 0.05
MINCONTRIB : 0
STARTWITH : c(4, 5, 6, 8, 9)
RESETSTART : TRUE
SHOWDETAIL : FALSE
CONTPLOT : histo
CVGROUPS : 5
RESOLUTION : 2500
STDERROR : TRUE
FAM : binomial

=========================================

########################################################################################
GRASP: Generalized Regression Analysis and Spatial Prediction for R, v2.0
Copyrights: Landcare Research New Zealand & Swiss Centre for Faunal Cartography, 1999-2005
Ref: A. Lehmann, J.R. Leathwick & J.McC. Overton, 2002. GRASP. Ecological Modelling, 157: 189-207
########################################################################################
_
platform i686-pc-linux-gnu
arch i686
os linux-gnu
system i686, linux-gnu
status
major 2
minor 7.1
year 2008
month 06
day 23
svn rev 45970
language R
version.string R version 2.7.1 (2008-06-23)
Fri Jul 4 03:26:51 2008
========== SELECTED VARIABLES ===========
selected responses: 2 3
selected predictors: 4 5 6 8 9
============================================
========== SET OPTIONS ===========
GRASP:
TITLE : GRASP:
PATH :
PATHPNG :
PATHLOG :
PATHLUT :
PLOTPAR : c(3, 3)
NBAR : 10
NPAST : 10
LIM : and
SELXLIM : c(4, 5, 6, 8, 9)
CORLIM : 1
RECALCULATEWEIGHTS : TRUE
CORTHIN : 1
CORPLOT : TRUE
DF1 : c(NA, NA, NA, NA, NA, NA, NA, NA, NA)
DF2 : c(4, 4, 4, 4, 4, 4, 4, 4, 4)
SMOOTHER : s
TEST : AIC
PERCONT : FALSE
DIRECTION : both
P.limit : 0.05
MINCONTRIB : 0
STARTWITH : c(4, 5, 6, 8, 9)
RESETSTART : TRUE
SHOWDETAIL : FALSE
CONTPLOT : histo
CVGROUPS : 5
RESOLUTION : 2500
STDERROR : TRUE
FAM : binomial
abscol : grey
prescol : black
PNG : FALSE

=========================================

INFO: !!! Applying DATAFILTER !!!
Number of observations used applying datafilter:
SP1 SP2
7563 7563

INFO: !!! WEIGHTS: sum of weights of 0s = sum of weights of 1s
Weights of 0s for SP1 = 0.05998598
Weights of 0s for SP2 = 0.11994669

VVVVVVVVVVVV calculating summaries VVVVVVVVVVVV
#
# FUNCTION: grasp.exp.summary
# (by A. Lehmann using Splus summary function)
# calculate a summary of selected Ys and Xs
#

vvvvvvvvvv GRASP SUMMARY vvvvvvvvvv
Fri Jul 4 03:26:51 2008
Y:
RESPONSE NAME: SP1
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.00000 0.00000 0.00000 0.05659 0.00000 1.00000

XXX:
TEMP RAD PREC SLOPE ASPECT
Min. : 529 Min. :1970 Min. : 323 Min. : 0.00 NORTH:1844
1st Qu.:1313 1st Qu.:5584 1st Qu.: 924 1st Qu.: 3.00 NULL :1636
Median :1622 Median :6440 Median :1175 Median :12.00 SOUTH:4083
Mean :1533 Mean :6741 Mean :1179 Mean :13.21
3rd Qu.:1803 3rd Qu.:7844 3rd Qu.:1434 3rd Qu.:22.00
Max. :2186 Max. :9772 Max. :2377 Max. :55.00
********** GRASP SUMMARY END **********

#
# FUNCTION: grasp.exp.summary
# (by A. Lehmann using Splus summary function)
# calculate a summary of selected Ys and Xs
#

vvvvvvvvvv GRASP SUMMARY vvvvvvvvvv
Fri Jul 4 03:26:51 2008
Y:
RESPONSE NAME: SP2
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.0000 0.0000 0.0000 0.1071 0.0000 1.0000

XXX:
TEMP RAD PREC SLOPE ASPECT
Min. : 529 Min. :1970 Min. : 323 Min. : 0.00 NORTH:1844
1st Qu.:1313 1st Qu.:5584 1st Qu.: 924 1st Qu.: 3.00 NULL :1636
Median :1622 Median :6440 Median :1175 Median :12.00 SOUTH:4083
Mean :1533 Mean :6741 Mean :1179 Mean :13.21
3rd Qu.:1803 3rd Qu.:7844 3rd Qu.:1434 3rd Qu.:22.00
Max. :2186 Max. :9772 Max. :2377 Max. :55.00
********** GRASP SUMMARY END **********

Fri Jul 4 03:26:51 2008

############ summaries calculated ############

VVVVVVVVVVVV plotting maps VVVVVVVVVVVV
#
# FUNCTION: grasp.exp.datamap
# (by J.R. Leathwick, adapted by A. Lehmann)
# maps the Predictor Variable(RV) point surveys for a spatial check of input data
#

vvvvvvvvvv GRASP DATAMAP vvvvvvvvvv
Fri Jul 4 03:26:51 2008
RESPONSE NAME: SP1

********** GRASP DATAMAP END **********

#
# FUNCTION: grasp.exp.datamap
# (by J.R. Leathwick, adapted by A. Lehmann)
# maps the Predictor Variable(RV) point surveys for a spatial check of input data
#

vvvvvvvvvv GRASP DATAMAP vvvvvvvvvv
Fri Jul 4 03:26:51 2008
RESPONSE NAME: SP2

********** GRASP DATAMAP END **********

Fri Jul 4 03:26:51 2008

############ map produced ############

VVVVVVVVVVVV histogram of response VVVVVVVVVVVV
#
# FUNCTION: grasp.exp.distry
# (by A. Lehmann)
# plot an histogram of the distribution of the Response Variable (RV)
#

vvvvvvvvvv HISTOGRAM OF RESPONSE vvvvvvvvvv
Fri Jul 4 03:26:51 2008
RESPONSE NAME: SP1
********** RESPONSE HISTOGRAM END **********

#
# FUNCTION: grasp.exp.distry
# (by A. Lehmann)
# plot an histogram of the distribution of the Response Variable (RV)
#

vvvvvvvvvv HISTOGRAM OF RESPONSE vvvvvvvvvv
Fri Jul 4 03:26:51 2008
RESPONSE NAME: SP2
********** RESPONSE HISTOGRAM END **********

Fri Jul 4 03:26:51 2008

############ histogram produced ############

VVVVVVVVVVVV plotting histograms VVVVVVVVVVVV
#
# FUNCTION: grasp.exp.histo
# (by J.R. Leathwick, adapted by A. Lehmann)
# calculates the distribution of the Response Variable (RV) on the histograms of Predictor Variables
#

vvvvvvvvvv GRASP HISTOGRAM vvvvvvvvvv
Fri Jul 4 03:26:51 2008
RESPONSE NAME: SP1
********** GRASP HISTOGRAM END **********

#
# FUNCTION: grasp.exp.histo
# (by J.R. Leathwick, adapted by A. Lehmann)
# calculates the distribution of the Response Variable (RV) on the histograms of Predictor Variables
#

vvvvvvvvvv GRASP HISTOGRAM vvvvvvvvvv
Fri Jul 4 03:26:51 2008
RESPONSE NAME: SP2
********** GRASP HISTOGRAM END **********

Fri Jul 4 03:26:51 2008

############ histograms produced ############

VVVVVVVVVVVV plotting response versus predictors VVVVVVVVVVVV
#
# FUNCTION: grasp.exp.RvsP
# (by A. Lehmann, requested by M. Ausin
# calculates the distribution of the response variable (RV) on the histograms of Predictor Variables
#
#

vvvvvvvvvv GRASP RESPONSE VS PREDICTORS vvvvvvvvvv
Fri Jul 4 03:26:51 2008
RESPONSE NAME: SP1

********** GRASP RESPONSE VS PREDICTORS END **********

#
# FUNCTION: grasp.exp.RvsP
# (by A. Lehmann, requested by M. Ausin
# calculates the distribution of the response variable (RV) on the histograms of Predictor Variables
#
#

vvvvvvvvvv GRASP RESPONSE VS PREDICTORS vvvvvvvvvv
Fri Jul 4 03:26:52 2008
RESPONSE NAME: SP2

********** GRASP RESPONSE VS PREDICTORS END **********

Fri Jul 4 03:26:53 2008

############ response versus predictors produced ############

VVVVVVVVVVVV plotting correlation matrix VVVVVVVVVVVV
#
# FUNCTION: grasp.exp.cormat
# (adapted from Mike Austin and Simon Barry, CSIRO, Australia)
# plot a correlation matrix of the Predictor Variables
#

vvvvvvvvvv GRASP CORMAT vvvvvvvvvv
Fri Jul 4 03:26:53 2008
RESPONSE NAME: SP1
STARTING MATRIX:
TEMP RAD PREC SLOPE
TEMP 0.0000000 -0.8846795 -0.2750157 -0.4397058
RAD -0.8846795 0.0000000 0.2562090 0.3755221
PREC -0.2750157 0.2562090 0.0000000 0.1455481
SLOPE -0.4397058 0.3755221 0.1455481 0.0000000
TEMP RAD PREC SLOPE
UNCORRELATED MATRIX:
TEMP RAD PREC SLOPE
TEMP 0.0000000 -0.8846795 -0.2750157 -0.4397058
RAD -0.8846795 0.0000000 0.2562090 0.3755221
PREC -0.2750157 0.2562090 0.0000000 0.1455481
SLOPE -0.4397058 0.3755221 0.1455481 0.0000000

********** GRASP CORMAT END **********

#
# FUNCTION: grasp.exp.cormat
# (adapted from Mike Austin and Simon Barry, CSIRO, Australia)
# plot a correlation matrix of the Predictor Variables
#

vvvvvvvvvv GRASP CORMAT vvvvvvvvvv
Fri Jul 4 03:26:54 2008
RESPONSE NAME: SP2
STARTING MATRIX:
TEMP RAD PREC SLOPE
TEMP 0.0000000 -0.8846795 -0.2750157 -0.4397058
RAD -0.8846795 0.0000000 0.2562090 0.3755221
PREC -0.2750157 0.2562090 0.0000000 0.1455481
SLOPE -0.4397058 0.3755221 0.1455481 0.0000000
TEMP RAD PREC SLOPE
UNCORRELATED MATRIX:
TEMP RAD PREC SLOPE
TEMP 0.0000000 -0.8846795 -0.2750157 -0.4397058
RAD -0.8846795 0.0000000 0.2562090 0.3755221
PREC -0.2750157 0.2562090 0.0000000 0.1455481
SLOPE -0.4397058 0.3755221 0.1455481 0.0000000

********** GRASP CORMAT END **********

Fri Jul 4 03:26:55 2008

############ correlation matrix plotted ############

VVVVVVVVVVVV mapping XXXpred predictors VVVVVVVVVVVV
#
# FUNCTION: grasp.int.xpredplot
# (by J.R. Leathwick, adapted by A. Lehmann)
# maps the spatial predictors contained in XXXpred
#

vvvvvvvvvv GRASP XXXpred PLOT vvvvvvvvvv
Fri Jul 4 03:26:55 2008
maxX: 837500
minX: 490000
maxY: 297500
minY: 77500
Nrow: 140
Ncol: 89
There are no duplicated X and Y coordinates in prediction set !

********** GRASP XXXpred PLOT END **********

#
# FUNCTION: grasp.int.xpredplot
# (by J.R. Leathwick, adapted by A. Lehmann)
# maps the spatial predictors contained in XXXpred
#

vvvvvvvvvv GRASP XXXpred PLOT vvvvvvvvvv
Fri Jul 4 03:26:55 2008
maxX: 837500
minX: 490000
maxY: 297500
minY: 77500
Nrow: 140
Ncol: 89
There are no duplicated X and Y coordinates in prediction set !

********** GRASP XXXpred PLOT END **********

#
# FUNCTION: grasp.int.xpredplot
# (by J.R. Leathwick, adapted by A. Lehmann)
# maps the spatial predictors contained in XXXpred
#

vvvvvvvvvv GRASP XXXpred PLOT vvvvvvvvvv
Fri Jul 4 03:26:55 2008
maxX: 837500
minX: 490000
maxY: 297500
minY: 77500
Nrow: 140
Ncol: 89
There are no duplicated X and Y coordinates in prediction set !

********** GRASP XXXpred PLOT END **********

#
# FUNCTION: grasp.int.xpredplot
# (by J.R. Leathwick, adapted by A. Lehmann)
# maps the spatial predictors contained in XXXpred
#

vvvvvvvvvv GRASP XXXpred PLOT vvvvvvvvvv
Fri Jul 4 03:26:55 2008
maxX: 837500
minX: 490000
maxY: 297500
minY: 77500
Nrow: 140
Ncol: 89
There are no duplicated X and Y coordinates in prediction set !

********** GRASP XXXpred PLOT END **********

#
# FUNCTION: grasp.int.xpredplot
# (by J.R. Leathwick, adapted by A. Lehmann)
# maps the spatial predictors contained in XXXpred
#

vvvvvvvvvv GRASP XXXpred PLOT vvvvvvvvvv
Fri Jul 4 03:26:56 2008
maxX: 837500
minX: 490000
maxY: 297500
minY: 77500
Nrow: 140
Ncol: 89
There are no duplicated X and Y coordinates in prediction set !

********** GRASP XXXpred PLOT END **********

Fri Jul 4 03:26:56 2008

############ XXXpred mapped ############

VVVVVVVVVVVV estimating models VVVVVVVVVVVV
#
# FUNCTION: grasp.step
# (by A. Lehmann and J.McC. Overton)
# selects a statistically significant model that explains a response variable by stepwise procedure
# based either on AIC criteria or on ANOVA tests with Chisq or F tests
#
Warning in MODELCALLS.local[[gr.Yi]]$gamcall <- NULL :
Coercing LHS to a list

vvvvvvvvvv GRASP STEP vvvvvvvvvv
Fri Jul 4 03:26:56 2008
RESPONSE NAME: SP1
#
# FUNCTION: grasp.step.scope (by A. Lehmann)
# generates automatically a model scope
#
#
# FUNCTION: grasp.step.start (by A. Lehmann)
# generates automatically a starting model formula
#
####################################
STEPWISE SELECTION:
####################################
DIRECTION: both

*******************
STARTING GAM MODEL:
*******************
Call:
gam(formula = YYY$SP1 ~ s(TEMP, 4) + s(RAD, 4) + s(PREC, 4) +
s(SLOPE, 4) + ASPECT, family = binomial, data = XXX, weights = WEIGHTS[,
2], subset = gr.modmask[, 2], na.action = na.omit, bf.maxit = 1000,
bf.epsilon = 0.001)

Degrees of Freedom: 7562 total; 7543.999 Residual
Residual Deviance: 656.3858
Null Deviance: 1186.668
D2: 0.4468665

####################################

AIC SELECTION:

######## SELECTION SUMMARY #########
Stepwise Model Path
Analysis of Deviance Table

Initial Model:
YYY$SP1 ~ s(TEMP, 4) + s(RAD, 4) + s(PREC, 4) + s(SLOPE, 4) +
ASPECT

Final Model:
YYY$SP1 ~ s(TEMP, 4) + s(RAD, 4) + s(PREC, 4) + s(SLOPE, 4) +
ASPECT

Scale: 0.09452684

From To Df Deviance Resid. Df Resid. Dev AIC
[1,] 1.0 1.0 7544 656.4 6541.3
####################################

*******************
SELECTED GAM MODEL:
*******************
gam(formula = YYY$SP1 ~ s(TEMP, 4) + s(RAD, 4) + s(PREC, 4) +
s(SLOPE, 4) + ASPECT, family = binomial, data = XXX, weights = WEIGHTS[,
2], subset = gr.modmask[, 2], na.action = na.omit, bf.maxit = 1000,
bf.epsilon = 0.001)

Distribution family: binomial
Selection method: AIC
Null Deviance: 1186.668
Explained Deviance: 530.2822
D2: 0.4468665
COR: 0.3588548
Number of presences: 428
Number of absences: 7135
Prevalence: 0.0565913
Weights of presences: 1
Weights of absences: 0.05998598
Weighted prevalence: 0.5

INFO: !!! Model formula saved in MODELCALLS[[2]]

********** GRASP STEP END **********

#
# FUNCTION: grasp.step
# (by A. Lehmann and J.McC. Overton)
# selects a statistically significant model that explains a response variable by stepwise procedure
# based either on AIC criteria or on ANOVA tests with Chisq or F tests
#
Warning in MODELCALLS.local[[gr.Yi]]$gamcall <- NULL :
Coercing LHS to a list

vvvvvvvvvv GRASP STEP vvvvvvvvvv
Fri Jul 4 03:27:09 2008
RESPONSE NAME: SP2
#
# FUNCTION: grasp.step.scope (by A. Lehmann)
# generates automatically a model scope
#
#
# FUNCTION: grasp.step.start (by A. Lehmann)
# generates automatically a starting model formula
#
####################################
STEPWISE SELECTION:
####################################
DIRECTION: both

*******************
STARTING GAM MODEL:
*******************
Call:
gam(formula = YYY$SP2 ~ s(TEMP, 4) + s(RAD, 4) + s(PREC, 4) +
s(SLOPE, 4) + ASPECT, family = binomial, data = XXX, weights = WEIGHTS[,
3], subset = gr.modmask[, 3], na.action = na.omit, bf.maxit = 1000,
bf.epsilon = 0.001)

Degrees of Freedom: 7562 total; 7544.001 Residual
Residual Deviance: 1743.479
Null Deviance: 2245.797
D2: 0.22367

####################################

AIC SELECTION:

######## SELECTION SUMMARY #########
Stepwise Model Path
Analysis of Deviance Table

Initial Model:
YYY$SP2 ~ s(TEMP, 4) + s(RAD, 4) + s(PREC, 4) + s(SLOPE, 4) +
ASPECT

Final Model:
YYY$SP2 ~ s(TEMP, 4) + s(RAD, 4) + s(SLOPE, 4)

Scale: 0.2001840

From To Df Deviance Resid. Df Resid. Dev AIC
[1,] 1.00 1.00 7544.0015 1743.48 1047.68
[2,] 2.00 1.00 1.9983 2.37 7545.9997 1745.85 1043.32
[3,] 3.00 1.00 4.0008 23.86 7550.0005 1769.71 1043.16
####################################

*******************
SELECTED GAM MODEL:
*******************
gam(formula = YYY$SP2 ~ s(TEMP, 4) + s(RAD, 4) + s(SLOPE, 4),
family = binomial, data = XXX, weights = WEIGHTS[, 3], subset = gr.modmask[,
3], na.action = na.omit, bf.maxit = 1000, bf.epsilon = 0.001,
trace = FALSE)

Distribution family: binomial
Selection method: AIC
Null Deviance: 2245.797
Explained Deviance: 476.0869
D2: 0.2119902
COR: 0.3114565
Number of presences: 810
Number of absences: 6753
Prevalence: 0.1071004
Weights of presences: 1
Weights of absences: 0.1199467
Weighted prevalence: 0.5

INFO: !!! Model formula saved in MODELCALLS[[3]]

********** GRASP STEP END **********

Fri Jul 4 03:27:26 2008

############ models estimated ############

VVVVVVVVVVVV calculating anova VVVVVVVVVVVV
GRASP:
#
# FUNCTION: grasp.mod.anova
# (by A. Lehmann
# calculates the ANOVA table of a selected model by droping each term one after the other form the full model
#

vvvvvvvvvv GRASP ANOVA vvvvvvvvvv
Fri Jul 4 03:27:30 2008
Selected Model for: SP1
gam(formula = YYY$SP1 ~ s(TEMP, 4) + s(RAD, 4) + s(PREC, 4) +
s(SLOPE, 4) + ASPECT, family = binomial, data = XXX, weights = WEIGHTS[,
2], subset = gr.modmask[, 2], na.action = na.omit, bf.maxit = 1000,
bf.epsilon = 0.001)
Null Deviance: 1186.668
Residual Deviance: 656.3858
Residual Df: 7543.999
D2: 0.4468665

Droping Resid. Df Resid. Dev Df Deviance P(>|Chi|)
2 - s(TEMP, 4) 7548.000 679.2633 -4.001278 -22.877538 1.341425e-04
21 - s(RAD, 4) 7547.998 664.1253 -3.999124 -7.739528 1.015468e-01
22 - s(PREC, 4) 7548.002 678.7724 -4.002592 -22.386617 1.683064e-04
23 - s(SLOPE, 4) 7547.998 700.1963 -3.999007 -43.810523 7.014823e-09
24 - ASPECT 7545.999 660.4097 -2.000059 -4.023845 1.337378e-01

********** GRASP ANOVA END **********

#
# FUNCTION: grasp.mod.anova
# (by A. Lehmann
# calculates the ANOVA table of a selected model by droping each term one after the other form the full model
#

vvvvvvvvvv GRASP ANOVA vvvvvvvvvv
Fri Jul 4 03:27:43 2008
Selected Model for: SP2
gam(formula = YYY$SP2 ~ s(TEMP, 4) + s(RAD, 4) + s(SLOPE, 4),
family = binomial, data = XXX, weights = WEIGHTS[, 3], subset = gr.modmask[,
3], na.action = na.omit, bf.maxit = 1000, bf.epsilon = 0.001,
trace = FALSE)
Null Deviance: 2245.797
Residual Deviance: 1769.71
Residual Df: 7550.001
D2: 0.2119902

Droping Resid. Df Resid. Dev Df Deviance P(>|Chi|)
2 - s(TEMP, 4) 7554.000 1907.519 -3.999341 -137.80879 8.301528e-29
21 - s(RAD, 4) 7554.000 1793.846 -3.999459 -24.13597 7.497148e-05
22 - s(SLOPE, 4) 7554.001 1801.004 -4.000700 -31.29392 2.668761e-06

********** GRASP ANOVA END **********

Fri Jul 4 03:27:45 2008
############ anova calculated ############

VVVVVVVVVVVV validating models VVVVVVVVVVVV
#
# FUNCTION: grasp.mod.validate
# (by A. Lehmann)
# calculates and plots validation and cross-validation statistics
#

vvvvvvvvvv GRASP VALIDATE vvvvvvvvvv
Fri Jul 4 03:27:50 2008
RESPONSE NAME: SP1
cv ROC auc: 0.886
cv COR: 0.355
ROC auc: 0.89
COR: 0.359
ID SP1
null.dev NA 1186.6679731
resid.dev NA 656.3858073
D2 NA 0.4468665
df.residual NA 7543.9989618
n NA 7563.0000000
ROC NA 0.8900000
cvROC NA 0.8860000
COR NA 0.3590000
cvCOR NA 0.3550000

********** GRASP VALIDATE END **********

#
# FUNCTION: grasp.mod.validate
# (by A. Lehmann)
# calculates and plots validation and cross-validation statistics
#

vvvvvvvvvv GRASP VALIDATE vvvvvvvvvv
Fri Jul 4 03:28:07 2008
RESPONSE NAME: SP2
cv ROC auc: 0.782
cv COR: 0.3071
ROC auc: 0.786
COR: 0.3115
ID SP2
null.dev NA 2245.7968650
resid.dev NA 1769.7099406
D2 NA 0.2119902
df.residual NA 7550.0005451
n NA 7563.0000000
ROC NA 0.7860000
cvROC NA 0.7820000
COR NA 0.3115000
cvCOR NA 0.3071000

********** GRASP VALIDATE END **********

Fri Jul 4 03:28:16 2008

############ validations plotted ############

VVVVVVVVVVVV calculating contributions VVVVVVVVVVVV
#
# FUNCTION: grasp.int.contrib
# (by A. Lehmann
# calculates the contributions (DROP, MODEL and ALONE) of the selected variables
#

vvvvvvvvvv GRASP CONTRIBUTION vvvvvvvvvv
Fri Jul 4 03:28:18 2008
RESPONSE NAME: SP1
INFO: new data
s(TEMP, 4) s(RAD, 4) s(PREC, 4) s(SLOPE, 4) ASPECT
PREDICTORS: s(TEMP, 4) / s(RAD, 4) / s(PREC, 4) / s(SLOPE, 4) / ASPECT /

[,1] [,2] [,3]
s(TEMP, 4) 22.877538 410.56224 11.983294
s(RAD, 4) 7.739528 391.03392 6.741377
s(PREC, 4) 22.386617 33.07752 1.954762
s(SLOPE, 4) 43.810523 316.49511 2.939726
ASPECT 4.023845 104.81564 0.509988

********** GRASP CONTRIBUTION END **********

#
# FUNCTION: grasp.int.contrib
# (by A. Lehmann
# calculates the contributions (DROP, MODEL and ALONE) of the selected variables
#

vvvvvvvvvv GRASP CONTRIBUTION vvvvvvvvvv
Fri Jul 4 03:28:34 2008
RESPONSE NAME: SP2
s(TEMP, 4) s(RAD, 4) s(SLOPE, 4)
PREDICTORS: s(TEMP, 4) / s(RAD, 4) / s(SLOPE, 4) /

[,1] [,2] [,3]
s(TEMP, 4) 137.80879 415.2115 5.5282928
s(RAD, 4) 24.13597 303.8305 3.3979621
s(SLOPE, 4) 31.29392 141.4678 0.8426627

********** GRASP CONTRIBUTION END **********

Fri Jul 4 03:28:38 2008

INFO: !!! CONTRIBUTIONS saved in ALONE.CONTRIB, MODEL.CONTRIB and DROP.CONTRIB

############ contributions calculated ############

VVVVVVVVVVVV plotting contributions VVVVVVVVVVVV
#
# FUNCTION: grasp.int.contplot
# (by A. Lehmann)
# Barplots of predictor contributions
#

vvvvvvvvvv GRASP CONT PLOT vvvvvvvvvv
Fri Jul 4 03:28:43 2008

********** GRASP CONT PLOT END **********

#
# FUNCTION: grasp.int.contplot
# (by A. Lehmann)
# Barplots of predictor contributions
#

vvvvvvvvvv GRASP CONT PLOT vvvvvvvvvv
Fri Jul 4 03:28:46 2008

********** GRASP CONT PLOT END **********

Fri Jul 4 03:28:46 2008

############ contributions plotted ############

VVVVVVVVVVVV plotting models VVVVVVVVVVVV
#
# FUNCTION: grasp.int.plot
# (by A. Lehmann using Splus gam.plot function)
# plots the partial response curves of each response variable for each selected Predictor
#

vvvvvvvvvv GRASP PLOT vvvvvvvvvv
Fri Jul 4 03:28:51 2008
RESPONSE NAME: SP1
Error in FUN(2:3[[1L]], ...) : could not find function "plot.gam"
Calls: grasp -> lapply -> FUN
Execution halted