- using R version 2.7.1 Patched (2008-06-26 r45997)
- 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 x86_64-unknown-linux-gnu
arch x86_64
os linux-gnu
system x86_64, linux-gnu
status Patched
major 2
minor 7.1
year 2008
month 06
day 26
svn rev 45997
language R
version.string R version 2.7.1 Patched (2008-06-26 r45997)
Sat Jun 28 23:14:25 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
Sat Jun 28 23:14:25 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
Sat Jun 28 23:14:25 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 **********
Sat Jun 28 23:14:25 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
Sat Jun 28 23:14:25 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
Sat Jun 28 23:14:25 2008
RESPONSE NAME: SP2
********** GRASP DATAMAP END **********
Sat Jun 28 23:14:26 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
Sat Jun 28 23:14:26 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
Sat Jun 28 23:14:26 2008
RESPONSE NAME: SP2
********** RESPONSE HISTOGRAM END **********
Sat Jun 28 23:14:26 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
Sat Jun 28 23:14:26 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
Sat Jun 28 23:14:26 2008
RESPONSE NAME: SP2
********** GRASP HISTOGRAM END **********
Sat Jun 28 23:14:26 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
Sat Jun 28 23:14:26 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
Sat Jun 28 23:14:26 2008
RESPONSE NAME: SP2
********** GRASP RESPONSE VS PREDICTORS END **********
Sat Jun 28 23:14:27 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
Sat Jun 28 23:14:27 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
Sat Jun 28 23:14:28 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 **********
Sat Jun 28 23:14:29 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
Sat Jun 28 23:14:29 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
Sat Jun 28 23:14:29 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
Sat Jun 28 23:14:29 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
Sat Jun 28 23:14:29 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
Sat Jun 28 23:14:29 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 **********
Sat Jun 28 23:14:29 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]]$gamcall <- NULL :
Coercing LHS to a list
vvvvvvvvvv GRASP STEP vvvvvvvvvv
Sat Jun 28 23:14:29 2008
RESPONSE NAME: SP1
#
# FUNCTION: grasp.step.scope (by A. Lehmann)
# generates automatically a model scope
#
#
# FUNCTION: grasp.step.start (by A. Lehmann)
# generates automatically a starting model formula
#
####################################
STEPWISE SELECTION:
####################################
DIRECTION: both
*******************
STARTING GAM MODEL:
*******************
Call:
gam(formula = YYY$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
Sat Jun 28 23:14:40 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 **********
Sat Jun 28 23:14:54 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
Sat Jun 28 23:14:57 2008
Selected Model for: SP1
gam(formula = YYY$SP1 ~ s(TEMP, 4) + s(RAD, 4) + s(PREC, 4) +
s(SLOPE, 4) + ASPECT, family = binomial, data = XXX, weights = WEIGHTS[,
2], subset = gr.modmask[, 2], na.action = na.omit, bf.maxit = 1000,
bf.epsilon = 0.001)
Null Deviance: 1186.668
Residual Deviance: 656.3858
Residual Df: 7543.999
D2: 0.4468665
Droping Resid. Df Resid. Dev Df Deviance P(>|Chi|)
2 - s(TEMP, 4) 7548.000 679.2633 -4.001278 -22.877538 1.341425e-04
21 - s(RAD, 4) 7547.998 664.1253 -3.999124 -7.739528 1.015468e-01
22 - s(PREC, 4) 7548.002 678.7724 -4.002592 -22.386617 1.683064e-04
23 - s(SLOPE, 4) 7547.998 700.1963 -3.999007 -43.810523 7.014823e-09
24 - ASPECT 7545.999 660.4097 -2.000059 -4.023845 1.337378e-01
********** GRASP ANOVA END **********
#
# FUNCTION: grasp.mod.anova
# (by A. Lehmann
# calculates the ANOVA table of a selected model by droping each term one after the other form the full model
#
vvvvvvvvvv GRASP ANOVA vvvvvvvvvv
Sat Jun 28 23:15:06 2008
Selected Model for: SP2
gam(formula = YYY$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 **********
Sat Jun 28 23:15:08 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
Sat Jun 28 23:15:11 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
Sat Jun 28 23:15:22 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 **********
Sat Jun 28 23:15:28 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
Sat Jun 28 23:15:30 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
Sat Jun 28 23:15:41 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 **********
Sat Jun 28 23:15:45 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
Sat Jun 28 23:15:49 2008
********** GRASP CONT PLOT END **********
#
# FUNCTION: grasp.int.contplot
# (by A. Lehmann)
# Barplots of predictor contributions
#
vvvvvvvvvv GRASP CONT PLOT vvvvvvvvvv
Sat Jun 28 23:15:51 2008
********** GRASP CONT PLOT END **********
Sat Jun 28 23:15:51 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
Sat Jun 28 23:15:55 2008
RESPONSE NAME: SP1
Error in FUN(2:3[[1L]], ...) : could not find function "plot.gam"
Calls: grasp -> lapply -> FUN
Execution halted