* using log directory 'd:/Rcompile/CRANpkg/local/3.6/LinearDetect.Rcheck'
* using R version 3.6.3 (2020-02-29)
* using platform: x86_64-w64-mingw32 (64-bit)
* using session charset: ISO8859-1
* checking for file 'LinearDetect/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'LinearDetect' version '0.1.5'
* 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 'LinearDetect' can be installed ... OK
* 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 R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* loading checks for arch 'i386'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
** checking loading without being on the library search path ... OK
** checking use of S3 registration ... OK
* loading checks for arch 'x64'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
** checking loading without being on the library search path ... 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 ... [21s] OK
* checking Rd files ... OK
* 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 line endings in C/C++/Fortran sources/headers ... OK
* checking line endings in Makefiles ... OK
* checking compilation flags in Makevars ... OK
* checking for GNU extensions in Makefiles ... OK
* checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
* checking pragmas in C/C++ headers and code ... OK
* checking compiled code ... OK
* checking installed files from 'inst/doc' ... OK
* checking files in 'vignettes' ... OK
* checking examples ...
** running examples for arch 'i386' ... ERROR
Running examples in 'LinearDetect-Ex.R' failed
The error most likely occurred in:

> ### Name: tbfl
> ### Title: Threshold block fused lasso (TBFL) algorithm for change point
> ###   detection
> ### Aliases: tbfl
> 
> ### ** Examples
> 
> #### constant model
> TT <- 10^3; # number of observations/samples
> p.y <- 50; # dimension of observed Y
> brk <- c(floor(TT/3),floor(2*TT/3), TT+1)
> m <- length(brk)
> d <- 5 #number of non-zero coefficient
> ### generate coefficient
> constant.full <- matrix(0, p.y, m)
> set.seed(1)
> constant.full[sample(1:p.y, d, replace = FALSE), 1] <- runif(d, -1, -0.5);
> constant.full[sample(1:p.y, d, replace = FALSE), 2] <- runif(d, 0.5, 1);
> constant.full[sample(1:p.y, d, replace = FALSE), 3] <- runif(d, -1, -0.5);
> e.sigma <- as.matrix(1*diag(p.y))
> try <- constant.sim.break(nobs = TT, cnst = constant.full, sigma = e.sigma, brk = brk)
> data_y <- try$series_y; data_y <- as.matrix(data_y, ncol = p.y)
> ### Fit the model
> method <- c("Constant")
> temp <- tbfl(method, data_y, block.size = 40, optimal.block = FALSE) #use a single block size
[1] "block sizes"
 [1] 80 80 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 80 80
[1] "block size"
[1] 40
[1] "cv.index:"
[1]  4  8 12 16 20
[1] 1
[1] "##################lambda1:"
[1] 401.8868
[1] "##################lambda2:"
[1] 0.6254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 1.025186
[1] "===================================="
[1] 2
[1] "##################lambda1:"
[1] 144.4306
[1] "##################lambda2:"
[1] 0.6254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 1.008716
[1] "===================================="
[1] 3
[1] "##################lambda1:"
[1] 51.90568
[1] "##################lambda2:"
[1] 0.6254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9978732
[1] "===================================="
[1] 4
[1] "##################lambda1:"
[1] 18.65393
[1] "##################lambda2:"
[1] 0.6254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9938887
[1] "===================================="
[1] 5
[1] "##################lambda1:"
[1] 6.703876
[1] "##################lambda2:"
[1] 0.6254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9947952
[1] "===================================="
[1] 6
[1] "##################lambda1:"
[1] 2.409248
[1] "##################lambda2:"
[1] 0.6254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9961026
[1] "===================================="
[1] 7
[1] "##################lambda1:"
[1] 0.8658388
[1] "##################lambda2:"
[1] 0.6254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.996265
[1] "===================================="
[1] 8
[1] "##################lambda1:"
[1] 0.3111663
[1] "##################lambda2:"
[1] 0.6254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9958982
[1] "===================================="
[1] 9
[1] "##################lambda1:"
[1] 0.1118274
[1] "##################lambda2:"
[1] 0.6254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9957791
[1] "===================================="
[1] 10
[1] "##################lambda1:"
[1] 0.04018868
[1] "##################lambda2:"
[1] 0.6254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9958029
[1] "===================================="
[1] 11
[1] "##################lambda1:"
[1] 401.8868
[1] "##################lambda2:"
[1] 0.06254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 1.025186
[1] "===================================="
[1] 12
[1] "##################lambda1:"
[1] 144.4306
[1] "##################lambda2:"
[1] 0.06254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 1.004269
[1] "===================================="
[1] 13
[1] "##################lambda1:"
[1] 51.90568
[1] "##################lambda2:"
[1] 0.06254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9678177
[1] "===================================="
[1] 14
[1] "##################lambda1:"
[1] 18.65393
[1] "##################lambda2:"
[1] 0.06254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9510438
[1] "===================================="
[1] 15
[1] "##################lambda1:"
[1] 6.703876
[1] "##################lambda2:"
[1] 0.06254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9481294
[1] "===================================="
[1] 16
[1] "##################lambda1:"
[1] 2.409248
[1] "##################lambda2:"
[1] 0.06254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9447256
[1] "===================================="
[1] 17
[1] "##################lambda1:"
[1] 0.8658388
[1] "##################lambda2:"
[1] 0.06254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9441555
[1] "===================================="
[1] 18
[1] "##################lambda1:"
[1] 0.3111663
[1] "##################lambda2:"
[1] 0.06254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9440089
[1] "===================================="
[1] 19
[1] "##################lambda1:"
[1] 0.1118274
[1] "##################lambda2:"
[1] 0.06254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9437034
[1] "===================================="
[1] 20
[1] "##################lambda1:"
[1] 0.04018868
[1] "##################lambda2:"
[1] 0.06254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.943712
[1] "===================================="
[1] 21
[1] "##################lambda1:"
[1] 401.8868
[1] "##################lambda2:"
[1] 0.006254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 1.025186
[1] "===================================="
[1] 22
[1] "##################lambda1:"
[1] 144.4306
[1] "##################lambda2:"
[1] 0.006254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 1.003713
[1] "===================================="
[1] 23
[1] "##################lambda1:"
[1] 51.90568
[1] "##################lambda2:"
[1] 0.006254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9674787
[1] "===================================="
[1] 24
[1] "##################lambda1:"
[1] 18.65393
[1] "##################lambda2:"
[1] 0.006254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9537906
[1] "===================================="
[1] 25
[1] "##################lambda1:"
[1] 6.703876
[1] "##################lambda2:"
[1] 0.006254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9533223
[1] "===================================="
[1] 26
[1] "##################lambda1:"
[1] 2.409248
[1] "##################lambda2:"
[1] 0.006254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9563411
[1] "===================================="
[1] 27
[1] "##################lambda1:"
[1] 0.8658388
[1] "##################lambda2:"
[1] 0.006254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.957752
[1] "===================================="
[1] 28
[1] "##################lambda1:"
[1] 0.3111663
[1] "##################lambda2:"
[1] 0.006254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9588602
[1] "===================================="
[1] 29
[1] "##################lambda1:"
[1] 0.1118274
[1] "##################lambda2:"
[1] 0.006254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9600366
[1] "===================================="
[1] 30
[1] "##################lambda1:"
[1] 0.04018868
[1] "##################lambda2:"
[1] 0.006254617
[1] "All coefficients are piecewise constant!"
[1] "============cv-result======================="
[1] 0.9610222
[1] "===================================="
[1] "All cv:"
 [1] 1.0251863 1.0087156 0.9978732 0.9938887 0.9947952 0.9961026 0.9962650
 [8] 0.9958982 0.9957791 0.9958029 1.0251863 1.0042694 0.9678177 0.9510438
[15] 0.9481294 0.9447256 0.9441555 0.9440089 0.9437034 0.9437120 1.0251863
[22] 1.0037127 0.9674787 0.9537906 0.9533223 0.9563411 0.9577520 0.9588602
[29] 0.9600366 0.9610222
[1] "Use BIC!"
[1] "Use BIC!"
[1] "small number of cp !!!!"
[1] "Cluster: 1"
[1] 321
[1] "Cluster: 2"
[1] 641 681
[1] "First step DONE!!!!+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++"
[1] "cp.final:"
[1] 333 666
[1] "Second step DONE!!!++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++"
[1] "no refit!"
> temp$cp.final
[1] 333 666
> temp$beta.final
[[1]]
 [1]  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
 [7]  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
[13]  0.0000000 -0.7058880  0.0000000  0.0000000  0.0000000  0.0000000
[19]  0.0000000  0.0000000  0.0000000  0.0000000 -1.1593873  0.0000000
[25]  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
[31]  0.0000000  0.0000000 -0.7169640  0.0000000  0.0000000  0.0000000
[37]  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
[43] -0.9256323  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
[49]  0.0000000  0.0000000

[[2]]
 [1]  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
 [7]  1.0206999  0.0000000  0.8150900  0.5548061  0.0000000  0.0000000
[13]  0.0000000  0.0000000  1.0615466  0.0000000  0.0000000  0.0000000
[19]  0.0000000  0.0000000  0.9893644  0.0000000  0.0000000  0.0000000
[25] -0.5288655  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
[31]  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
[37]  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
[43]  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
[49]  0.0000000  0.0000000

[[3]]
 [1]  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
 [7]  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
[13]  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
[19]  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
[25] -1.1662868  0.0000000  0.0000000  0.0000000  0.0000000  0.0000000
[31]  0.0000000  0.0000000  0.0000000 -0.7604442  0.0000000  0.0000000
[37] -0.9873347  0.0000000  0.0000000  0.0000000  0.0000000 -0.7722985
[43]  0.0000000 -0.8151191  0.0000000  0.0000000  0.0000000  0.0000000
[49]  0.0000000  0.0000000

> 
> 
> 
> 
> #### multiple linear regression
> TT <- 2*10^3; # number of observations/samples
> p.y <- 1; # dimension of observed Y
> p.x <- 20
> brk <- c(floor(TT/4), floor(2*TT/4), floor(3*TT/4), TT+1)
> m <- length(brk)
> d <- 15 #number of non-zero coefficient
> ###generate coefficient beta
> beta.full <- matrix(0, p.y, p.x*m)
> set.seed(1)
> aa <- c(-3, 5, -3, 3)
> for(i in 1:m){beta.full[1, (i-1)*p.x+sample(1:p.x, d, replace = FALSE)] <- aa[i] + runif(d, -1, 1);}
> e.sigma <- as.matrix(1*diag(p.y))
> try <- lm.sim.break(nobs = TT, px = p.x, phi = beta.full, sigma = e.sigma, sigma_x = 1, brk = brk)
> data_y <- try$series_y; data_y <- as.matrix(data_y, ncol = p.y)
> data_x <- try$series_x; data_x <- as.matrix(data_x)
> ### Fit the model
> method <- c("MLR")
> 
> 
> 
> 
> #### Gaussian Graphical model
> TT <- 3*10^3; # number of observations/samples
> p.x <- 20 # dimension of obsrved X
> # TRUE BREAK POINTS WITH T+1 AS THE LAST ELEMENT
> brk <- c(floor(TT/3), floor(2*TT/3), TT+1)
> m <- length(brk)
> ###generate precision matrix and covariance matrix
> eta = 0.1
> d <- ceiling(p.x*eta)
> sigma.full <- matrix(0, p.x, p.x*m)
> omega.full <- matrix(0, p.x, p.x*m)
> aa <- 1/d
> for(i in 1:m){
+ if(i%%2==1){
+ ajmatrix <- matrix(0, p.x, p.x)
+ for(j in 1:(floor(p.x/5)) ){
+ ajmatrix[ ((j-1)*5+1): (5*j), ((j-1)*5+1): (5*j)] <- 1
+ }
+ }
+ if(i%%2==0){
+ ajmatrix <- matrix(0, p.x, p.x)
+ for(j in 1:(floor(p.x/10)) ){
+ ajmatrix[ seq(((j-1)*10+1), (10*j), 2), seq(((j-1)*10+1), (10*j), 2)] <- 1
+ ajmatrix[ seq(((j-1)*10+2), (10*j), 2), seq(((j-1)*10+2), (10*j), 2)] <- 1
+ }
+ }
+ theta <- aa* ajmatrix
+ # force it to be positive definite
+ if(min(eigen(theta)$values) <= 0){
+ print('add noise')
+ theta = theta - (min(eigen(theta)$values)-0.05) * diag(p.x)
+ }
+ sigma.full[, ((i-1)*p.x+1):(i*p.x)]  <- as.matrix(solve(theta))
+ omega.full[, ((i-1)*p.x+1):(i*p.x)]  <- as.matrix(theta)
+ }
Error in solve.default(theta) : 
  Lapack routine dgesv: system is exactly singular: U[2,2] = 0
Calls: as.matrix -> solve -> solve.default
Execution halted
** running examples for arch 'x64' ... [9s] OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in 'inst/doc' ... OK
* checking re-building of vignette outputs ... [4s] OK
* checking PDF version of manual ... OK
* DONE
Status: 1 ERROR