R Under development (unstable) (2023-08-30 r85030 ucrt) -- "Unsuffered Consequences" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(GGMselect) Loading required package: mvtnorm > > p=50 > n=60 > eta=0.092 > extraeta=eta/5 > Gr <- list(NULL) > iG=1 > set.seed(iG) > Gr[[iG]] <- simulateGraph(p,eta,extraeta=extraeta) > X <- rmvnorm(n, mean=rep(0,p), sigma=Gr[[iG]]$C) > X <- scale(X,center=TRUE,scale=FALSE) > #Gr.Chap10 <- selectFast(X, verbose=T, dmax=10, K=2.5, family="C01") > #Gr.Chap25 <- selectFast(X, verbose=T,dmax=25, K=2.5, family="C01") > print( selectFast(X,verbose=T, dmax=26, K=2.5, family="C01")) *** Run family C01 *** End family C01 $C01 $C01$Neighb [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 11 0 0 0 0 0 0 0 0 0 0 0 0 0 3 7 38 6 0 0 0 0 0 0 0 0 0 0 0 4 13 0 0 0 0 0 0 0 0 0 0 0 0 0 5 49 25 0 0 0 0 0 0 0 0 0 0 0 0 6 35 16 3 0 0 0 0 0 0 0 0 0 0 0 7 3 27 38 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 27 0 0 0 0 0 0 0 0 0 0 0 0 0 10 14 0 0 0 0 0 0 0 0 0 0 0 0 0 11 2 41 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 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0 49 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 50 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 > # gc(verbose=FALSE) > # ----------------------------------------------------- > p=50 > n=1000 > eta=0.092 > extraeta=eta/5 > Gr <- list(NULL) > iG=1 > set.seed(iG) > Gr[[iG]] <- simulateGraph(p,eta,extraeta=extraeta) > X <- rmvnorm(n, mean=rep(0,p), sigma=Gr[[iG]]$C) > X <- scale(X,center=TRUE,scale=FALSE) > print( selectFast(X, dmax=10, K=2.5, family="C01")) $C01 $C01$Neighb [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] 1 0 0 0 0 0 0 0 0 0 0 2 11 0 0 0 0 0 0 0 0 0 3 7 38 6 35 0 0 0 0 0 0 4 13 0 0 0 0 0 0 0 0 0 5 49 38 0 0 0 0 0 0 0 0 6 35 16 41 3 13 0 0 0 0 0 7 3 27 38 9 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 9 27 7 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 0 0 0 11 2 41 0 0 0 0 0 0 0 0 12 0 0 0 0 0 0 0 0 0 0 13 4 6 0 0 0 0 0 0 0 0 14 37 0 0 0 0 0 0 0 0 0 15 17 0 0 0 0 0 0 0 0 0 16 6 22 35 0 0 0 0 0 0 0 17 15 30 0 0 0 0 0 0 0 0 18 50 0 0 0 0 0 0 0 0 0 19 30 0 0 0 0 0 0 0 0 0 20 26 0 0 0 0 0 0 0 0 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0 1 0 0 0 0 43 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 45 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 46 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 47 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 48 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 49 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 50 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 > # ----------------------------------------------------- > p=60 > n=60 > eta=0.092 > extraeta=eta/5 > Gr <- list(NULL) > iG=1 > set.seed(iG) > Gr[[iG]] <- simulateGraph(p,eta,extraeta=extraeta) > X <- rmvnorm(n, mean=rep(0,p), sigma=Gr[[iG]]$C) > X <- scale(X,center=TRUE,scale=FALSE) > print( selectFast(X,verbose=T, dmax=10, K=2.5, family="C01")) *** Run family C01 *** End family C01 $C01 $C01$Neighb [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] 1 38 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 6 11 0 0 0 0 0 0 0 0 0 7 18 0 0 0 0 0 0 0 0 0 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39 0 0 0 0 0 0 0 40 0 0 0 0 0 0 0 41 0 0 0 0 0 0 0 42 0 0 0 0 0 0 0 43 0 0 0 0 0 0 0 44 0 0 0 0 0 0 0 45 0 0 0 0 0 0 0 46 0 0 0 0 0 0 0 47 0 0 0 0 0 0 1 48 0 0 0 0 0 0 0 49 0 0 0 0 0 0 0 50 0 0 0 0 0 0 0 51 0 0 0 0 0 0 0 52 0 0 0 0 0 0 0 53 0 0 0 0 0 0 0 54 0 0 0 0 0 0 0 55 0 0 0 0 0 0 1 56 0 0 0 0 0 0 0 57 0 0 0 0 0 0 0 58 0 0 0 0 0 0 0 59 0 0 0 0 0 0 0 60 0 1 0 0 0 0 0 > # ----------------------------------------------------- > p=60 > n=1000 > eta=0.092 > extraeta=eta/5 > Gr <- list(NULL) > iG=1 > set.seed(iG) > Gr[[iG]] <- simulateGraph(p,eta,extraeta=extraeta) > X <- rmvnorm(n, mean=rep(0,p), sigma=Gr[[iG]]$C) > X <- scale(X,center=TRUE,scale=FALSE) > print(selectFast(X, dmax=10, K=2.5, family="C01")) $C01 $C01$Neighb [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] 1 38 14 12 0 0 0 0 0 0 0 2 12 0 0 0 0 0 0 0 0 0 3 39 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 5 30 0 0 0 0 0 0 0 0 0 6 11 12 15 0 0 0 0 0 0 0 7 18 0 0 0 0 0 0 0 0 0 8 9 0 0 0 0 0 0 0 0 0 9 50 36 8 0 0 0 0 0 0 0 10 19 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31 0 0 0 0 0 0 0 32 0 0 0 0 0 0 0 33 0 0 1 0 0 0 0 34 0 0 0 0 0 0 0 35 0 0 0 0 0 0 0 36 0 0 0 0 0 0 0 37 0 0 0 0 0 0 0 38 0 0 0 0 0 0 0 39 0 0 0 0 0 0 0 40 0 0 0 0 0 0 0 41 0 0 0 0 0 0 0 42 0 0 0 0 0 0 0 43 0 0 0 0 0 0 0 44 0 0 0 0 0 0 0 45 0 0 0 0 0 0 0 46 0 0 0 0 0 0 0 47 0 0 0 0 0 0 1 48 0 0 0 1 0 0 0 49 0 0 0 0 0 0 0 50 1 0 0 0 0 1 0 51 0 0 0 0 1 0 0 52 0 0 0 0 0 0 0 53 1 0 0 0 0 0 0 54 0 0 1 1 0 1 0 55 0 0 0 0 0 0 1 56 1 0 0 1 0 0 0 57 1 0 1 0 0 1 0 58 0 0 0 0 0 0 0 59 1 0 0 1 0 0 0 60 0 1 0 0 0 0 0 > # ----------------------------------------------------- > p=60 > n=1000 > eta=0.092 > extraeta=eta/5 > Gr <- list(NULL) > iG=1 > set.seed(iG) > Gr[[iG]] <- simulateGraph(p,eta,extraeta=extraeta) > X <- rmvnorm(n, mean=rep(0,p), sigma=Gr[[iG]]$C) > X <- scale(X,center=TRUE,scale=FALSE) > print(selectFast(X, dmax=26, K=2.5, family="C01")) $C01 $C01$Neighb [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] 1 38 14 12 0 0 0 0 0 0 0 0 0 0 0 2 12 0 0 0 0 0 0 0 0 0 0 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