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Don't use symlinks in tests/birds_Biometrics.R
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,98 @@ | ||
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| library("mboostDevel") | ||
| data("birds", package = "TH.data") | ||
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| # define characteristics of the boosting algorithm | ||
| bcr <- boost_control(mstop=200, trace=TRUE) | ||
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| # estimation of a purely linear GLM | ||
| fm <- SG5 ~ bols(GST) + bols(DBH) + bols(AOT) + bols(AFS) + bols(DWC) + | ||
| bols(LOG) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
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| # extract and plot AIC curve against iteration index and determine stopping | ||
| # iteration | ||
| birdsaic <- AIC(sp, "classical") | ||
| plot(birdsaic) | ||
| ms <- mstop(birdsaic) | ||
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| # selection frequencies of the model terms | ||
| table(sp$xselect()[1:ms]) | ||
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| # estimated coefficients | ||
| coef(sp[ms]) | ||
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| # re-define boosting iterations | ||
| bcr <- boost_control(mstop=500, trace=TRUE) | ||
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| # Variable selection in a GLM without spatial component | ||
| fm <- SG4 ~ bols(GST) + bols(DBH) + bols(AOT) + bols(AFS) + bols(DWC) + | ||
| bols(LOG) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
| table(sp$xselect()) | ||
| coef(sp, which=1:6) | ||
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| # Variable selection in a GLM with high df spatial component | ||
| fm <- SG4 ~ bols(GST) + bols(DBH) + bols(AOT) + bols(AFS) + bols(DWC) + | ||
| bols(LOG) + bspatial(x_gk, y_gk, df=5, differences=1, knots=c(12,12)) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
| table(sp$xselect()) | ||
| coef(sp, which=1:6) | ||
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| # Variable selection in a GLM with small df spatial component | ||
| fm <- SG4 ~ bols(GST) + bols(DBH) + bols(AOT) + bols(AFS) + bols(DWC) + | ||
| bols(LOG) + bspatial(x_gk, y_gk, df=1, differences=1, knots=c(12,12), center=TRUE) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
| table(sp$xselect()) | ||
| coef(sp, which=1:6) | ||
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| # Geoadditive regression model without centering | ||
| fm <- SG5 ~ bbs(GST) + bbs(DBH) + bbs(AOT) + bbs(AFS) + bbs(DWC) + | ||
| bbs(LOG) + bspatial(x_gk, y_gk, df=4, differences=1, knots=c(12,12)) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
| plot(sp) | ||
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| # Geoadditive regression model with centering | ||
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| fm <- SG5 ~ bols(GST) + bbs(GST, df=1, center=TRUE) + | ||
| bols(AOT) + bbs(AOT, df=1, center=TRUE) + | ||
| bols(AFS) + bbs(AFS, df=1, center=TRUE) + | ||
| bols(DWC) + bbs(DWC, df=1, center=TRUE) + | ||
| bols(LOG) + bbs(LOG, df=1, center=TRUE) + | ||
| bspatial(x_gk, y_gk, df=1, differences=1, knots=c(12,12), | ||
| center=TRUE) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
| plot(sp) | ||
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| # re-define boosting iterations | ||
| bcr <- boost_control(mstop=200, trace=TRUE) | ||
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| # transform covariates to [0,1] | ||
| birds$GST <- (birds$GST-min(birds$GST))/(max(birds$GST)-min(birds$GST)) | ||
| birds$AOT <- (birds$AOT-min(birds$AOT))/(max(birds$AOT)-min(birds$AOT)) | ||
| birds$AFS <- (birds$AFS-min(birds$AFS))/(max(birds$AFS)-min(birds$AFS)) | ||
| birds$DWC <- (birds$DWC-min(birds$DWC))/(max(birds$DWC)-min(birds$DWC)) | ||
| birds$LOG <- (birds$LOG-min(birds$LOG))/(max(birds$LOG)-min(birds$LOG)) | ||
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| # Space-varying coefficient models (with centered spatial effects) | ||
| fm <- SG5 ~ bols(GST) + bspatial(x_gk, y_gk, by = GST, df=1, differences=1, | ||
| knots=c(12, 12), center=TRUE) + | ||
| bols(AOT) + bspatial(x_gk, y_gk, by = AOT, df=1, differences=1, | ||
| knots=c(12, 12), center=TRUE) + | ||
| bols(AFS) + bspatial(x_gk, y_gk, by = AFS, df=1, differences=1, | ||
| knots=c(12, 12), center=TRUE) + | ||
| bols(DWC) + bspatial(x_gk, y_gk, by = DWC, df=1, differences=1, | ||
| knots=c(12, 12), center=TRUE) + | ||
| bols(LOG) + bspatial(x_gk, y_gk, by = LOG, df=1, differences=1, | ||
| knots=c(12, 12), center=TRUE) + | ||
| bspatial(x_gk, y_gk, df=1, differences=1, knots=c(12, 12), | ||
| center=TRUE) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
| plot(sp, which = "GST") | ||
| plot(sp, which = "AOT") | ||
| plot(sp, which = "AFS") | ||
| plot(sp, which = "DWC") | ||
| plot(sp, which = "LOG") | ||
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|
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,98 @@ | ||
|
|
||
| library("mboost") | ||
| data("birds", package = "TH.data") | ||
|
|
||
| # define characteristics of the boosting algorithm | ||
| bcr <- boost_control(mstop=200, trace=TRUE) | ||
|
|
||
| # estimation of a purely linear GLM | ||
| fm <- SG5 ~ bols(GST) + bols(DBH) + bols(AOT) + bols(AFS) + bols(DWC) + | ||
| bols(LOG) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
|
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| # extract and plot AIC curve against iteration index and determine stopping | ||
| # iteration | ||
| birdsaic <- AIC(sp, "classical") | ||
| plot(birdsaic) | ||
| ms <- mstop(birdsaic) | ||
|
|
||
| # selection frequencies of the model terms | ||
| table(sp$xselect()[1:ms]) | ||
|
|
||
| # estimated coefficients | ||
| coef(sp[ms]) | ||
|
|
||
| # re-define boosting iterations | ||
| bcr <- boost_control(mstop=500, trace=TRUE) | ||
|
|
||
| # Variable selection in a GLM without spatial component | ||
| fm <- SG4 ~ bols(GST) + bols(DBH) + bols(AOT) + bols(AFS) + bols(DWC) + | ||
| bols(LOG) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
| table(sp$xselect()) | ||
| coef(sp, which=1:6) | ||
|
|
||
| # Variable selection in a GLM with high df spatial component | ||
| fm <- SG4 ~ bols(GST) + bols(DBH) + bols(AOT) + bols(AFS) + bols(DWC) + | ||
| bols(LOG) + bspatial(x_gk, y_gk, df=5, differences=1, knots=c(12,12)) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
| table(sp$xselect()) | ||
| coef(sp, which=1:6) | ||
|
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||
| # Variable selection in a GLM with small df spatial component | ||
| fm <- SG4 ~ bols(GST) + bols(DBH) + bols(AOT) + bols(AFS) + bols(DWC) + | ||
| bols(LOG) + bspatial(x_gk, y_gk, df=1, differences=1, knots=c(12,12), center=TRUE) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
| table(sp$xselect()) | ||
| coef(sp, which=1:6) | ||
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||
|
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| # Geoadditive regression model without centering | ||
| fm <- SG5 ~ bbs(GST) + bbs(DBH) + bbs(AOT) + bbs(AFS) + bbs(DWC) + | ||
| bbs(LOG) + bspatial(x_gk, y_gk, df=4, differences=1, knots=c(12,12)) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
| plot(sp) | ||
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| # Geoadditive regression model with centering | ||
|
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| fm <- SG5 ~ bols(GST) + bbs(GST, df=1, center=TRUE) + | ||
| bols(AOT) + bbs(AOT, df=1, center=TRUE) + | ||
| bols(AFS) + bbs(AFS, df=1, center=TRUE) + | ||
| bols(DWC) + bbs(DWC, df=1, center=TRUE) + | ||
| bols(LOG) + bbs(LOG, df=1, center=TRUE) + | ||
| bspatial(x_gk, y_gk, df=1, differences=1, knots=c(12,12), | ||
| center=TRUE) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
| plot(sp) | ||
|
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||
|
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| # re-define boosting iterations | ||
| bcr <- boost_control(mstop=200, trace=TRUE) | ||
|
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| # transform covariates to [0,1] | ||
| birds$GST <- (birds$GST-min(birds$GST))/(max(birds$GST)-min(birds$GST)) | ||
| birds$AOT <- (birds$AOT-min(birds$AOT))/(max(birds$AOT)-min(birds$AOT)) | ||
| birds$AFS <- (birds$AFS-min(birds$AFS))/(max(birds$AFS)-min(birds$AFS)) | ||
| birds$DWC <- (birds$DWC-min(birds$DWC))/(max(birds$DWC)-min(birds$DWC)) | ||
| birds$LOG <- (birds$LOG-min(birds$LOG))/(max(birds$LOG)-min(birds$LOG)) | ||
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| # Space-varying coefficient models (with centered spatial effects) | ||
| fm <- SG5 ~ bols(GST) + bspatial(x_gk, y_gk, by = GST, df=1, differences=1, | ||
| knots=c(12, 12), center=TRUE) + | ||
| bols(AOT) + bspatial(x_gk, y_gk, by = AOT, df=1, differences=1, | ||
| knots=c(12, 12), center=TRUE) + | ||
| bols(AFS) + bspatial(x_gk, y_gk, by = AFS, df=1, differences=1, | ||
| knots=c(12, 12), center=TRUE) + | ||
| bols(DWC) + bspatial(x_gk, y_gk, by = DWC, df=1, differences=1, | ||
| knots=c(12, 12), center=TRUE) + | ||
| bols(LOG) + bspatial(x_gk, y_gk, by = LOG, df=1, differences=1, | ||
| knots=c(12, 12), center=TRUE) + | ||
| bspatial(x_gk, y_gk, df=1, differences=1, knots=c(12, 12), | ||
| center=TRUE) | ||
| sp <- gamboost(fm, data = birds, family = Poisson(), control = bcr) | ||
| plot(sp, which = "GST") | ||
| plot(sp, which = "AOT") | ||
| plot(sp, which = "AFS") | ||
| plot(sp, which = "DWC") | ||
| plot(sp, which = "LOG") | ||
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