1## SSANOVA, GSSANOVA, SSDEN, SSCDEN, SSLLRM, SSHZD, AND SSCOX SUITES 2ssanova Fitting smoothing spline ANOVA models 3predict.ssanova Predicting from ssanova fits 4predict1.ssanova Predicting from ssanova fits 5summary.ssanova Summarizing ssanova fits 6project.ssanova Projecting ssanova fits for model diagnostic 7ssanova9 Fitting smoothing spline ANOVA models with correlated data 8summary.ssanova9 Summarizing ssanova9 fits 9project.ssanova9 Projecting ssanova9 fits for model diagnostic 10ssanova0 Fitting smoothing spline ANOVA models 11predict.ssanova0 Predicting from ssanova0 fits 12summary.ssanova0 Summarizing ssanova0 fits 13residuals.ssanova Extracting the residuals from ssanova objects 14fitted.ssanova Extracting the fitted values from ssanova objects 15print.ssanova Print function for ssanova objects 16print.ssanova0 Print function for ssanova0 objects 17print.summary.ssanova Print function for summary.ssanova objects 18 19gssanova Fitting smoothing spline ANOVA models with non Gaussian data 20gssanova1 Fitting smoothing spline ANOVA models with non Gaussian data 21predict9.gssanova Predicting from gssanova fits 22summary.gssanova Summarizing gssanova fits 23project.gssanova Projecting gssanova1 fits for model diagnostic 24gssanova0 Fitting smoothing spline ANOVA models with non Gaussian data 25summary.gssanova0 Summarizing gssanova0 fits 26residuals.gssanova Extracting the residuals from gssanova objects 27fitted.gssanova Extracting the fitted values from gssanova objects 28print.gssanova Print function for gssanova objects 29print.summary.gssanova Print function for summary.gssanova objects 30print.summary.gssanova0 Print function for summary.gssanova0 objects 31 32ssden Estimating probability density using smoothing splines 33d.ssden Evaluating pdf of ssden estimates 34project.ssden Projecting ssden fits for model diagnostic 35ssden1 Estimating probability density using smoothing splines 36d.ssden1 Evaluating pdf of ssden1 estimates 37project.ssden1 Projecting ssden1 fits for model diagnostic 38dssden Evaluating pdf of ssden estimates 39pssden Evaluating cdf of 1-D ssden estimates 40qssden Evaluating quantiles of 1-D ssden estimates 41cdssden Evaluating conditional pdf of ssden estimates 42cpssden Evaluating 1-D conditional cdf of ssden estimates 43cqssden Evaluating 1-D conditional quantiles of ssden estimates 44print.ssden Print function for ssden objects 45sscomp Estimating composition with one sample 46sscomp2 Estimating composition with multiple samples 47 48sscden Estimating conditional density using smoothing splines 49d.sscden Evaluating pdf of sscden estimates 50project.sscden Projecting sscden fits for model diagnostic 51sscden1 Estimating conditional density using smoothing splines 52d.sscden1 Evaluating pdf of sscden1 estimates 53project.sscden1 Projecting sscden1 fits for model diagnostic 54dsscden Evaluating pdf of sscden estimates 55psscden Evaluating cdf of sscden estimates with 1-D Y 56qsscden Evaluating quantiles of ssden estimates with 1-D Y 57cdsscden Evaluating conditional pdf of sscden estimates 58cpsscden Evaluating 1-D conditional cdf of sscden estimates 59cqsscden Evaluating 1-D conditional quantiles of sscden estimates 60print.sscden Print function for sscden objects 61 62ssllrm Fitting smoothing spline log-linear regression models 63predict.ssllrm Evaluating log-linear regression model fits 64project.ssllrm Projecting ssllrm fits for model diagnostic 65print.ssllrm Print function for ssllrm objects 66 67sshzd Estimating hazard function using smoothing splines 68project.sshzd Projecting sshzd fits for model diagnostic 69sshzd1 Estimating hazard function using smoothing splines 70project.sshzd1 Projecting sshzd1 fits for model diagnostic 71hzdrate.sshzd Evaluating hazard estimates 72hzdcurve.sshzd Evaluating hazard curves 73survexp.sshzd Computing expected survivals 74print.sshzd Print function for sshzd objects 75 76sscox Estimating relative risk using smoothing splines 77predict.sscox Projecting sscox fits for model diagnostic 78project.sscox Predicting from sscox fits 79print.sscox Print function for sscox objects 80 81## SSCOPU, SSCOPU2, SSHZD2D, AND SSHZD2D1 SUITES 82sscopu Fitting copula density using smoothing splines 83sscopu2 Fitting 2-D copula density using smoothing splines 84dsscopu Evaluating pdf of sscopu estimates 85cdsscopu Evaluating 1-D conditional pdf of sscopu estimates 86cpsscopu Evaluating 1-D conditional cdf of sscopu estimates 87cqsscopu Evaluating 1-D conditional quantiles of sscopu estimates 88summary.sscopu Calculating Kendall's tau and Spearman's rho of sscopu estimates 89print.sscopu Print function for sscopu objects 90 91sshzd2d Estimating 2-D hazard function using smoothing splines 92sshzd2d1 Estimating 2-D hazard function using smoothing splines 93hzdrate.sshzd2d Evaluating 2-D hazard estimates 94survexp.sshzd2d Evaluating 2-D survival estimates 95print.sshzd2d Print function for sshzd2d objects 96 97## UTILITIES FOR MAKING MODEL TERMS 98mkterm Making model terms 99mkterm.copu Making model terms for sscopu/sscopu2 100 101mkphi.cubic Making phi function for cubic splines 102mkrk.cubic Making RK function for cubic splines 103mkrk.cubic.per Making RK function for periodic cubic splines 104mkrk.linear Making RK function for linear splines 105mkrk.linear.per Making RK function for periodic linear splines 106 107mkphi.tp Making phi functions for thin-plate splines 108mkphi.tp.p Making pseudo phi functions for thin-plate splines 109mkrk.tp Making RK functions for thin-plate splines 110mkrk.tp.p Making pseudo RK functions for thin-plate splines 111mkrk.sphere Making RK functions for spherical splines 112 113mkrk.nominal Making RK function for nominal factors 114mkrk.ordinal Making RK function for ordinal factors 115 116mkran Generating random effects in mixed-effect models 117mkran1 Combining random effects in mixed-effect models 118 119mkcov.arma Making covariance function for ARMA models 120mkcov.long Making covariance function for longitudinal data 121mkcov.known Passing known covariance function to ssanova9 122 123mkint Generating integrals of basis terms for ssden1 suite 124mkint2 Generating integrals of basis terms for ssden1 suite 125 126## UTILITIES FOR DISTRIBUTION FAMILIES 127mkdata.binomial Making pseudo data for logistic regression 128dev.resid.binomial Deviance residuals for logistic regression 129dev.null.binomial Null model deviance for logistic regression 130cv.binomial CV score for logistic regression 131y0.binomial Preparing for KL projection of logistic fit 132proj0.binomial Making pseudo data for projection of logistic fit 133kl.binomial Computing KL distance between logistic fits 134cfit.binomial Computing constant logistic fit 135 136mkdata.poisson Making pseudo data for Poisson regression 137dev.resid.poisson Deviance residuals for Poisson regression 138dev.null.poisson Null model deviance for Poisson regression 139cv.poisson CV score for Poisson regression 140y0.poisson Preparing for KL projection of Poisson fit 141proj0.poisson Making pseudo data for projection of Poisson fit 142kl.poisson Computing KL distance between Poisson fits 143cfit.poisson Computing constant Poisson fit 144 145mkdata.Gamma Making pseudo data for Gamma regression 146dev.resid.Gamma Deviance residuals for Gamma regression 147dev.null.Gamma Null model deviance for Gamma regression 148cv.Gamma CV score for Gamma regression 149y0.Gamma Preparing for KL projection of Gamma fit 150proj0.Gamma Making pseudo data for projection of Gamma fit 151kl.Gamma Computing KL distance between Gamma fits 152cfit.Gamma Computing constant Gamma fit 153 154mkdata.inverse.gaussian Making pseudo data for IG regression 155dev.resid.inverse.gaussian Deviance residuals for IG regression 156dev.null.inverse.gaussian Null model deviance for IG regression 157cv.inverse.gaussian CV score for IG regression 158y0.inverse.gaussian Preparing for KL projection of IG fit 159proj0.inverse.gaussian Making pseudo data for projection of IG fit 160kl.inverse.gaussian Computing KL distance between IG fits 161cfit.inverse.gaussian Computing constant IG fit 162 163mkdata.nbinomial Making pseudo data for negative binomial regression 164dev.resid.nbinomial Deviance residuals for negative binomial regression 165dev.null.nbinomial Null model deviance for negative binomial regression 166cv.nbinomial CV score for negative binomial regression 167y0.nbinomial Preparing for KL projection of negative binomial fit 168proj0.nbinomial Making pseudo data for projection of negative binomial fit 169kl.nbinomial Computing KL distance between negative binomial fits 170cfit.nbinomial Computing constant negative binomial fit 171 172mkdata.polr Making pseudo data for proportional odds regression 173dev.resid.polr Deviance residuals for proportional odds regression 174dev.null.polr Null model deviance for proportional odds regression 175cv.polr CV score for proportional odds regression 176y0.polr Preparing for KL projection of proportional odds fit 177proj0.polr Making pseudo data for projection of proportional odds fit 178kl.polr Computing KL distance between proportional odds fits 179cfit.polr Computing constant proportional odds fit 180 181mkdata.weibull Making pseudo data for Weibull regression 182dev.resid.weibull Deviance residuals for Weibull regression 183dev.null.weibull Null model deviance for Weibull regression 184cv.weibull CV score for Weibull regression 185y0.weibull Preparing for KL projection of Weibull fit 186proj0.weibull Making pseudo data for projection of Weibull fit 187kl.weibull Computing KL distance between Weibull fits 188cfit.weibull Computing constant Weibull fit 189 190mkdata.lognorm Making pseudo data for log normal regression 191dev.resid.lognorm Deviance residuals for log normal regression 192dev0.resid.lognorm Pseudo deviance residuals for log normal regression 193dev.null.lognorm Null model deviance for log normal regression 194cv.lognorm CV score for log normal regression 195y0.lognorm Preparing for KL projection of log normal fit 196proj0.lognorm Making pseudo data for projection of log normal fit 197kl.lognorm Computing KL distance between log normal fits 198cfit.lognorm Computing constant log normal fit 199 200mkdata.loglogis Making pseudo data for log logistic regression 201dev.resid.loglogis Deviance residuals for log logistic regression 202dev0.resid.loglogis Pseudo deviance residuals for log logistic regression 203dev.null.loglogis Null model deviance for log logistic regression 204cv.loglogis CV score for log logistic regression 205y0.loglogis Preparing for KL projection of log logistic fit 206proj0.loglogis Making pseudo data for projection of log logistic fit 207kl.loglogis Computing KL distance between log logistic fits 208cfit.loglogis Computing constant log logistic fit 209 210## UTILITIES FOR NUMERICAL INTEGRATION 211gauss.quad Generating Gauss-Legendre quadrature 212smolyak.quad Generating Smolyak cubature 213smolyak.size Getting the size of Smolyak cubature 214 215## UTILITY FOR OPTIMIZATION 216nlm0 Minimizing univariate functions on finite intervals 217 218## NUMERICAL ENGINE 219sspreg0 An interface to RKPACK driver DSIDR 220mspreg0 An interface to RKPACK driver DMUDR 221sspregpoi Performance-oriented iteration using RKPACK driver DSIDR 222mspregpoi Performance-oriented iteration using RKPACK driver DMUDR 223getcrdr An interface to RKPACK utility DCRDR 224getsms An interface to RKPACK utility DSMS 225 226sspreg1 Compute regression estimate with single smoothing parameter 227mspreg1 Compute regression estimate with multiple smoothing parameters 228sspreg91 Compute regression estimate with single smoothing parameter 229mspreg91 Compute regression estimate with multiple smoothing parameters 230sspngreg Compute NG regression estimate with single smoothing parameter 231mspngreg Compute NG regression estimate with single smoothing parameter 232ngreg Newton iteration for NG regression with fixed smoothing parameter 233ngreg1 Performance-oriented iteration using sspreg1 and mspreg1 234regaux Obtain auxiliary information needed for se calculation 235ngreg.proj Calculate Kullback-Leibler projection for NG regression 236 237sspdsty Compute density estimate with single smoothing parameter 238mspdsty Compute density estimate with multiple smoothing parameters 239sspdsty1 Compute density estimate with single smoothing parameter 240mspdsty1 Compute density estimate with multiple smoothing parameters 241mspcdsty Compute conditional density estimate 242mspcdsty1 Compute conditional density estimate 243msphzd Compute hazard estimate with single or multiple smoothing parameters 244msphzd1 Compute hazard estimate with single or multiple smoothing parameters 245sspcox Compute relative risk estimate with single smoothing parameter 246mspcox Compute relative risk estimate with multiple smoothing parameters 247 248mspllrm Compute log-linear regression model with multiple smoothing parameters 249 250mspcopu2 Compute 2-D copula density estimate under censoring/truncation 251