/usr/lib/R/site-library/gss/INDEX is in r-cran-gss 2.1-5-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 | ## SSANOVA, GSSANOVA, SSDEN, SSCDEN, SSLLRM, SSHZD, AND SSCOX SUITES
ssanova Fitting smoothing spline ANOVA models
predict.ssanova Predicting from ssanova fits
summary.ssanova Summarizing ssanova fits
project.ssanova Projecting ssanova fits for model diagnostic
ssanova9 Fitting smoothing spline ANOVA models with correlated data
summary.ssanova9 Summarizing ssanova9 fits
project.ssanova9 Projecting ssanova9 fits for model diagnostic
ssanova0 Fitting smoothing spline ANOVA models
predict.ssanova0 Predicting from ssanova0 fits
summary.ssanova0 Summarizing ssanova0 fits
residuals.ssanova Extracting the residuals from ssanova objects
fitted.ssanova Extracting the fitted values from ssanova objects
print.ssanova Print function for ssanova objects
print.ssanova0 Print function for ssanova0 objects
print.summary.ssanova Print function for summary.ssanova objects
gssanova Fitting smoothing spline ANOVA models with non Gaussian data
gssanova1 Fitting smoothing spline ANOVA models with non Gaussian data
summary.gssanova Summarizing gssanova fits
project.gssanova Projecting gssanova1 fits for model diagnostic
gssanova0 Fitting smoothing spline ANOVA models with non Gaussian data
summary.gssanova0 Summarizing gssanova0 fits
residuals.gssanova Extracting the residuals from gssanova objects
fitted.gssanova Extracting the fitted values from gssanova objects
print.gssanova Print function for gssanova objects
print.summary.gssanova Print function for summary.gssanova objects
print.summary.gssanova0 Print function for summary.gssanova0 objects
ssden Estimating probability density using smoothing splines
d.ssden Evaluating pdf of ssden estimates
project.ssden Projecting ssden fits for model diagnostic
ssden1 Estimating probability density using smoothing splines
d.ssden1 Evaluating pdf of ssden1 estimates
project.ssden1 Projecting ssden1 fits for model diagnostic
dssden Evaluating pdf of ssden estimates
pssden Evaluating cdf of 1-D ssden estimates
qssden Evaluating quantiles of 1-D ssden estimates
cdssden Evaluating conditional pdf of ssden estimates
cpssden Evaluating 1-D conditional cdf of ssden estimates
cqssden Evaluating 1-D conditional quantiles of ssden estimates
print.ssden Print function for ssden objects
sscden Estimating conditional density using smoothing splines
d.sscden Evaluating pdf of sscden estimates
project.sscden Projecting sscden fits for model diagnostic
sscden1 Estimating conditional density using smoothing splines
d.sscden1 Evaluating pdf of sscden1 estimates
project.sscden1 Projecting sscden1 fits for model diagnostic
dsscden Evaluating pdf of sscden estimates
psscden Evaluating cdf of sscden estimates with 1-D Y
qsscden Evaluating quantiles of ssden estimates with 1-D Y
cdsscden Evaluating conditional pdf of sscden estimates
cpsscden Evaluating 1-D conditional cdf of sscden estimates
cqsscden Evaluating 1-D conditional quantiles of sscden estimates
print.sscden Print function for sscden objects
ssllrm Fitting smoothing spline log-linear regression models
predict.ssllrm Evaluating log-linear regression model fits
project.ssllrm Projecting ssllrm fits for model diagnostic
print.ssllrm Print function for ssllrm objects
sshzd Estimating hazard function using smoothing splines
project.sshzd Projecting sshzd fits for model diagnostic
sshzd1 Estimating hazard function using smoothing splines
project.sshzd1 Projecting sshzd1 fits for model diagnostic
hzdrate.sshzd Evaluating hazard estimates
hzdcurve.sshzd Evaluating hazard curves
survexp.sshzd Computing expected survivals
print.sshzd Print function for sshzd objects
sscox Estimating relative risk using smoothing splines
predict.sscox Projecting sscox fits for model diagnostic
project.sscox Predicting from sscox fits
print.sscox Print function for sscox objects
## UTILITIES FOR MAKING MODEL TERMS
mkterm Making model terms
mkphi.cubic Making phi function for cubic splines
mkrk.cubic Making RK function for cubic splines
mkrk.cubic.per Making RK function for periodic cubic splines
mkrk.linear Making RK function for linear splines
mkrk.linear.per Making RK function for periodic linear splines
mkphi.tp Making phi functions for thin-plate splines
mkphi.tp.p Making pseudo phi functions for thin-plate splines
mkrk.tp Making RK functions for thin-plate splines
mkrk.tp.p Making pseudo RK functions for thin-plate splines
mkrk.sphere Making RK functions for spherical splines
mkrk.nominal Making RK function for nominal factors
mkrk.ordinal Making RK function for ordinal factors
mkran Generating random effects in mixed-effect models
mkcov.arma Making covariance function for ARMA models
mkcov.long Making covariance function for longitudinal data
mkcov.known Passing known covariance function to ssanova9
mkint Generating integrals of basis terms for ssden1 suite
mkint2 Generating integrals of basis terms for ssden1 suite
## UTILITIES FOR DISTRIBUTION FAMILIES
mkdata.binomial Making pseudo data for logistic regression
dev.resid.binomial Deviance residuals for logistic regression
dev.null.binomial Null model deviance for logistic regression
cv.binomial CV score for logistic regression
y0.binomial Preparing for KL projection of logistic fit
proj0.binomial Making pseudo data for projection of logistic fit
kl.binomial Computing KL distance between logistic fits
cfit.binomial Computing constant logistic fit
mkdata.poisson Making pseudo data for Poisson regression
dev.resid.poisson Deviance residuals for Poisson regression
dev.null.poisson Null model deviance for Poisson regression
cv.poisson CV score for Poisson regression
y0.poisson Preparing for KL projection of Poisson fit
proj0.poisson Making pseudo data for projection of Poisson fit
kl.poisson Computing KL distance between Poisson fits
cfit.poisson Computing constant Poisson fit
mkdata.Gamma Making pseudo data for gamma regression
dev.resid.Gamma Deviance residuals for gamma regression
dev.null.Gamma Null model deviance for gamma regression
cv.Gamma CV score for gamma regression
y0.Gamma Preparing for KL projection of Gamma fit
proj0.Gamma Making pseudo data for projection of Gamma fit
kl.Gamma Computing KL distance between Gamma fits
cfit.Gamma Computing constant Gamma fit
mkdata.inverse.gaussian Making pseudo data for IG regression
dev.resid.inverse.gaussian Deviance residuals for IG regression
dev.null.inverse.gaussian Null model deviance for IG regression
mkdata.nbinomial Making pseudo data for negative binomial regression
dev.resid.nbinomial Deviance residuals for negative binomial regression
dev.null.nbinomial Null model deviance for negative binomial regression
cv.nbinomial CV score for negative binomial regression
y0.nbinomial Preparing for KL projection of negative binomial fit
proj0.nbinomial Making pseudo data for projection of negative binomial fit
kl.nbinomial Computing KL distance between negative binomial fits
cfit.nbinomial Computing constant negative binomial fit
mkdata.weibull Making pseudo data for Weibull regression
dev.resid.weibull Deviance residuals for Weibull regression
dev.null.weibull Null model deviance for Weibull regression
cv.weibull CV score for Weibull regression
y0.weibull Preparing for KL projection of Weibull fit
proj0.weibull Making pseudo data for projection of Weibull fit
kl.weibull Computing KL distance between Weibull fits
cfit.weibull Computing constant Weibull fit
mkdata.lognorm Making pseudo data for log normal regression
dev.resid.lognorm Deviance residuals for log normal regression
dev0.resid.lognorm Pseudo deviance residuals for log normal regression
dev.null.lognorm Null model deviance for log normal regression
cv.lognorm CV score for log normal regression
y0.lognorm Preparing for KL projection of log normal fit
proj0.lognorm Making pseudo data for projection of log normal fit
kl.lognorm Computing KL distance between log normal fits
cfit.lognorm Computing constant log normal fit
mkdata.loglogis Making pseudo data for log logistic regression
dev.resid.loglogis Deviance residuals for log logistic regression
dev0.resid.loglogis Pseudo deviance residuals for log logistic regression
dev.null.loglogis Null model deviance for log logistic regression
cv.loglogis CV score for log logistic regression
y0.loglogis Preparing for KL projection of log logistic fit
proj0.loglogis Making pseudo data for projection of log logistic fit
kl.loglogis Computing KL distance between log logistic fits
cfit.loglogis Computing constant log logistic fit
## UTILITIES FOR NUMERICAL INTEGRATION
gauss.quad Generating Gauss-Legendre quadrature
smolyak.quad Generating Smolyak cubature
smolyak.size Getting the size of Smolyak cubature
## UTILITY FOR OPTIMIZATION
nlm0 Minimizing univariate functions on finite intervals
## NUMERICAL ENGINE
sspreg0 An interface to RKPACK driver DSIDR
mspreg0 An interface to RKPACK driver DMUDR
sspregpoi Performance-oriented iteration using RKPACK driver DSIDR
mspregpoi Performance-oriented iteration using RKPACK driver DMUDR
getcrdr An interface to RKPACK utility DCRDR
getsms An interface to RKPACK utility DSMS
sspreg1 Compute regression estimate with single smoothing parameter
mspreg1 Compute regression estimate with multiple smoothing parameters
sspreg91 Compute regression estimate with single smoothing parameter
mspreg91 Compute regression estimate with multiple smoothing parameters
sspngreg Compute NG regression estimate with single smoothing parameter
mspngreg Compute NG regression estimate with single smoothing parameter
ngreg Newton iteration for NG regression with fixed smoothing parameter
ngreg1 Performance-oriented iteration using sspreg1 and mspreg1
regaux Obtain auxiliary information needed for se calculation
ngreg.proj Calculate Kullback-Leibler projection for NG regression
sspdsty Compute density estimate with single smoothing parameter
mspdsty Compute density estimate with multiple smoothing parameters
sspdsty1 Compute density estimate with single smoothing parameter
mspdsty1 Compute density estimate with multiple smoothing parameters
mspcdsty Compute conditional density estimate
mspcdsty1 Compute conditional density estimate
msphzd Compute hazard estimate with single or multiple smoothing parameters
msphzd1 Compute hazard estimate with single or multiple smoothing parameters
sspcox Compute relative risk estimate with single smoothing parameter
mspcox Compute relative risk estimate with multiple smoothing parameters
mspllrm Compute log-linear regression model with multiple smoothing parameters
|