- using R version 4.4.0 RC (2024-04-16 r86468 ucrt)
- using platform: x86_64-w64-mingw32
- R was compiled by gcc.exe (GCC) 13.2.0 GNU Fortran (GCC) 13.2.0
- running under: Windows Server 2022 x64 (build 20348)
- using session charset: UTF-8
- checking for file 'DChaos/DESCRIPTION' ... OK
- checking extension type ... Package
- this is package 'DChaos' version '0.1-7'
- package encoding: UTF-8
- checking package namespace information ... OK
- checking package dependencies ... OK
- checking if this is a source package ... OK
- checking if there is a namespace ... OK
- checking for hidden files and directories ... OK
- checking for portable file names ... OK
- checking whether package 'DChaos' can be installed ... OK See the install log for details.
- checking installed package size ... OK
- checking package directory ... OK
- checking 'build' directory ... OK
- checking DESCRIPTION meta-information ... OK
- checking top-level files ... OK
- checking for left-over files ... OK
- checking index information ... OK
- checking package subdirectories ... OK
- checking code files for non-ASCII characters ... OK
- checking R files for syntax errors ... OK
- checking whether the package can be loaded ... [0s] OK
- checking whether the package can be loaded with stated dependencies ... [0s] OK
- checking whether the package can be unloaded cleanly ... [1s] OK
- checking whether the namespace can be loaded with stated dependencies ... [0s] OK
- checking whether the namespace can be unloaded cleanly ... [1s] OK
- checking loading without being on the library search path ... [0s] OK
- checking use of S3 registration ... OK
- checking 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 ... [5s] OK
- checking Rd files ... [1s] NOTE checkRd: (-1) lyapunov.Rd:57: Lost braces; missing escapes or markup? 57 | This function returns several objects considering the parameter set selected by the user. The largest Lyapunov exponent (Norma-2 procedure) and the Lyapunov exponent spectrum (QR decomposition procedure) by each blocking method are estimated. It also contains some useful information about the estimated jacobian, the best-fitted feed-forward single hidden layer neural net model, the best set of weights found, the fitted values, the residuals obtained, the best embedding parameters set chosen, the sample size or the block length considered by each blocking method. This function provides the standard error, the z test value and the p-value for testing the null hypothesis \eqn{H0: \lambda_k > 0 for k = 1,2,3, \ldots, m}. Reject the null hypothesis ${H_0}$ means lack of chaotic behaviour. That is, the data-generating process does not have a chaotic attractor because of it does not show the property of sensitivity to initial conditions. | ^ checkRd: (-1) lyapunov.max.Rd:24: Lost braces; missing escapes or markup? 24 | This function returns several objects considering the parameter set selected by the user. The largest Lyapunov exponent considering the Norma-2 procedure by each blocking method are estimated. It also contains some useful information about the estimated jacobian, the best-fitted feed-forward single hidden layer neural net model, the best set of weights found, the fitted values, the residuals obtained, the best embedding parameters set chosen, the sample size or the block length considered by each blocking method. This function provides the standard error, the z test value and the p-value for testing the null hypothesis \eqn{H0: \lambda_k > 0 for k = 1} (largest). Reject the null hypothesis ${H_0}$ means lack of chaotic behaviour. That is, the data-generating process does not have a chaotic attractor because of it does not show the property of sensitivity to initial conditions. | ^ checkRd: (-1) lyapunov.spec.Rd:24: Lost braces; missing escapes or markup? 24 | This function returns several objects considering the parameter set selected by the user. The Lyapunov exponent spectrum considering the QR decomposition procedure by each blocking method are estimated. It also contains some useful information about the estimated jacobian, the best-fitted feed-forward single hidden layer neural net model, the best set of weights found, the fitted values, the residuals obtained, the best embedding parameters set chosen, the sample size or the block length considered by each blocking method. This function provides the standard error, the z test value and the p-value for testing the null hypothesis \eqn{H0: \lambda_k > 0 for k = 1,2,3, \ldots, m} (full spectrum). Reject the null hypothesis ${H_0}$ means lack of chaotic behaviour. That is, the data-generating process does not have a chaotic attractor because of it does not show the property of sensitivity to initial conditions. | ^
- checking Rd metadata ... OK
- checking Rd cross-references ... OK
- checking for missing documentation entries ... OK
- checking for code/documentation mismatches ... OK
- checking Rd \usage sections ... OK
- checking Rd contents ... OK
- checking for unstated dependencies in examples ... OK
- checking sizes of PDF files under 'inst/doc' ... OK
- checking installed files from 'inst/doc' ... OK
- checking files in 'vignettes' ... OK
- checking examples ... [1s] OK
- checking for unstated dependencies in vignettes ... OK
- checking package vignettes ... OK
- checking re-building of vignette outputs ... [0s] OK
- checking PDF version of manual ... [20s] OK
- checking HTML version of manual ... [3s] OK
- DONE

Status: 1 NOTE