A B C D E F G H I K L M N P Q R S T U misc
AIC.nlrq | Function to compute nonlinear quantile regression estimates |
AIC.rq | Linear Quantile Regression Object |
AIC.rqs | Linear Quantile Regression Object |
AIC.rqss | RQSS Objects and Summarization Thereof |
akj | Density Estimation using Adaptive Kernel method |
anova.rq | Anova function for quantile regression fits |
anova.rqlist | Anova function for quantile regression fits |
anova.rqs | Anova function for quantile regression fits |
bandwidth.rq | bandwidth selection for rq functions |
barro | Barro Data |
boot.crq | Bootstrapping Censored Quantile Regression |
boot.rq | Bootstrapping Quantile Regression |
boot.rq.mcmb | Bootstrapping Quantile Regression |
boot.rq.pwxy | Preprocessing weighted bootstrap method |
boot.rq.pwy | Bootstrapping Quantile Regression |
boot.rq.pxy | Preprocessing bootstrap method |
boot.rq.spwy | Bootstrapping Quantile Regression |
boot.rq.wxy | Bootstrapping Quantile Regression |
boot.rq.xy | Bootstrapping Quantile Regression |
Bosco | Boscovich Data |
ChangeLog | FAQ and ChangeLog of a package |
CobarOre | Cobar Ore data |
coef.crq | Functions to fit censored quantile regression models |
coef.nlrq | Function to compute nonlinear quantile regression estimates |
combos | Ordered Combinations |
critval | Hotelling Critical Values |
crq | Functions to fit censored quantile regression models |
crq.fit.pen | Functions to fit censored quantile regression models |
crq.fit.por | Functions to fit censored quantile regression models |
crq.fit.por2 | Functions to fit censored quantile regression models |
crq.fit.pow | Functions to fit censored quantile regression models |
Curv | Functions to fit censored quantile regression models |
deviance.nlrq | Function to compute nonlinear quantile regression estimates |
dither | Function to randomly perturb a vector |
dynrq | Dynamic Linear Quantile Regression |
end.dynrq | Dynamic Linear Quantile Regression |
engel | Engel Data |
extractAIC.nlrq | Function to compute nonlinear quantile regression estimates |
extractAIC.rq | Linear Quantile Regression Object |
FAQ | FAQ and ChangeLog of a package |
fitted.nlrq | Function to compute nonlinear quantile regression estimates |
fitted.rqss | RQSS Objects and Summarization Thereof |
formula.nlrq | Function to compute nonlinear quantile regression estimates |
formula.rq | Linear Quantile Regression Object |
gasprice | Time Series of US Gasoline Prices |
Hill | Estimation and Inference on the Pareto Tail Exponent for Linear Models |
Hill.fit | Estimation and Inference on the Pareto Tail Exponent for Linear Models |
index.dynrq | Dynamic Linear Quantile Regression |
KhmaladzeTest | Tests of Location and Location Scale Shift Hypotheses for Linear Models |
kselect | Quicker Sample Quantiles |
kuantile | Quicker Sample Quantiles |
kunique | Quicker Sample Quantiles |
LassoLambdaHat | Lambda selection for QR lasso problems |
latex | Make a latex version of an R object |
latex.summary.rqs | Make a latex table from a table of rq results |
latex.table | Writes a latex formatted table to a file |
latex.table.rq | Table of Quantile Regression Results |
lm.fit.recursive | Recursive Least Squares |
logLik.nlrq | Function to compute nonlinear quantile regression estimates |
logLik.rq | Linear Quantile Regression Object |
logLik.rqs | Linear Quantile Regression Object |
logLik.rqss | RQSS Objects and Summarization Thereof |
lprq | locally polynomial quantile regression |
Mammals | Garland(1983) Data on Running Speed of Mammals |
MelTemp | Daily maximum temperatures in Melbourne, Australia |
Munge | Munge rqss formula |
nlrq | Function to compute nonlinear quantile regression estimates |
nlrq.control | Set control parameters for nlrq |
nlrqModel | Function to compute nonlinear quantile regression estimates |
ParetoTest | Estimation and Inference on the Pareto Tail Exponent for Linear Models |
Peirce | C.S. Peirce's Auditory Response Data |
Pickands | Estimation and Inference on the Pareto Tail Exponent for Linear Models |
Pickands.fit | Estimation and Inference on the Pareto Tail Exponent for Linear Models |
plot.KhmaladzeTest | Plot a KhmaladzeTest object |
plot.qss1 | Plot Method for rqss Objects |
plot.qss2 | Plot Method for rqss Objects |
plot.qts1 | Plot Method for rqss Objects |
plot.rq.process | plot the coordinates of the quantile regression process |
plot.rqs | Visualizing sequences of quantile regressions |
plot.rqss | Plot Method for rqss Objects |
plot.summary.crqs | Summary methods for Censored Quantile Regression |
plot.summary.rq | Visualizing sequences of quantile regression summaries |
plot.summary.rqs | Visualizing sequences of quantile regression summaries |
plot.summary.rqss | Plot Method for rqss Objects |
plot.table.rq | Table of Quantile Regression Results |
predict.crq | Functions to fit censored quantile regression models |
predict.crqs | Functions to fit censored quantile regression models |
predict.nlrq | Function to compute nonlinear quantile regression estimates |
predict.qss1 | Predict from fitted nonparametric quantile regression smoothing spline models |
predict.qss2 | Predict from fitted nonparametric quantile regression smoothing spline models |
predict.rq | Quantile Regression Prediction |
predict.rq.process | Quantile Regression Prediction |
predict.rqs | Quantile Regression Prediction |
predict.rqss | Predict from fitted nonparametric quantile regression smoothing spline models |
print.anova.rq | Anova function for quantile regression fits |
print.crq | Functions to fit censored quantile regression models |
print.dynrq | Dynamic Linear Quantile Regression |
print.dynrqs | Dynamic Linear Quantile Regression |
print.Hill | Estimation and Inference on the Pareto Tail Exponent for Linear Models |
print.KhmaladzeTest | Print a KhmaladzeTest object |
print.nlrq | Function to compute nonlinear quantile regression estimates |
print.Pickands | Estimation and Inference on the Pareto Tail Exponent for Linear Models |
print.rq | Print an rq object |
print.rqs | Print an rq object |
print.rqss | RQSS Objects and Summarization Thereof |
print.summary.crq | Summary methods for Censored Quantile Regression |
print.summary.crqs | Summary methods for Censored Quantile Regression |
print.summary.dynrq | Dynamic Linear Quantile Regression |
print.summary.dynrqs | Dynamic Linear Quantile Regression |
print.summary.Hill | Estimation and Inference on the Pareto Tail Exponent for Linear Models |
print.summary.nlrq | Function to compute nonlinear quantile regression estimates |
print.summary.Pickands | Estimation and Inference on the Pareto Tail Exponent for Linear Models |
print.summary.rq | Print Quantile Regression Summary Object |
print.summary.rqs | Print Quantile Regression Summary Object |
print.summary.rqss | Summary of rqss fit |
q489 | Even Quicker Sample Quantiles |
qrisk | Function to compute Choquet portfolio weights |
qss | Additive Nonparametric Terms for rqss Fitting |
qss1 | Additive Nonparametric Terms for rqss Fitting |
qss2 | Additive Nonparametric Terms for rqss Fitting |
QTECox | Function to obtain QTE from a Cox model |
qts1 | Additive Nonparametric Terms for rqss Fitting |
ranks | Quantile Regression Ranks |
rearrange | Rearrangement |
resid.rqss | RQSS Objects and Summarization Thereof |
residuals.nlrq | Return residuals of an nlrq object |
rq | Quantile Regression |
rq.fit | Function to choose method for Quantile Regression |
rq.fit.br | Quantile Regression Fitting by Exterior Point Methods |
rq.fit.conquer | Optional Fitting Method for Quantile Regression |
rq.fit.fnb | Quantile Regression Fitting via Interior Point Methods |
rq.fit.fnc | Quantile Regression Fitting via Interior Point Methods |
rq.fit.hogg | weighted quantile regression fitting |
rq.fit.lasso | Lasso Penalized Quantile Regression |
rq.fit.pfn | Preprocessing Algorithm for Quantile Regression |
rq.fit.pfnb | Quantile Regression Fitting via Interior Point Methods |
rq.fit.ppro | Preprocessing fitting method for QR |
rq.fit.qfnb | Quantile Regression Fitting via Interior Point Methods |
rq.fit.scad | SCADPenalized Quantile Regression |
rq.fit.sfn | Sparse Regression Quantile Fitting |
rq.fit.sfnc | Sparse Constrained Regression Quantile Fitting |
rq.object | Linear Quantile Regression Object |
rq.process.object | Linear Quantile Regression Process Object |
rq.test.anowar | Anova function for quantile regression fits |
rq.test.rank | Anova function for quantile regression fits |
rq.wfit | Function to choose method for Weighted Quantile Regression |
rqProcess | Compute Standardized Quantile Regression Process |
rqs.fit | Function to fit multiple response quantile regression models |
rqss | Additive Quantile Regression Smoothing |
rqss.fit | Additive Quantile Regression Smoothing |
rqss.object | RQSS Objects and Summarization Thereof |
sfn.control | Set Control Parameters for Sparse Fitting |
sfnMessage | Sparse Regression Quantile Fitting |
srisk | Markowitz (Mean-Variance) Portfolio Optimization |
start.dynrq | Dynamic Linear Quantile Regression |
summary.crq | Summary methods for Censored Quantile Regression |
summary.crqs | Summary methods for Censored Quantile Regression |
summary.dynrq | Dynamic Linear Quantile Regression |
summary.dynrqs | Dynamic Linear Quantile Regression |
summary.Hill | Estimation and Inference on the Pareto Tail Exponent for Linear Models |
summary.nlrq | Function to compute nonlinear quantile regression estimates |
summary.Pickands | Estimation and Inference on the Pareto Tail Exponent for Linear Models |
summary.rcrqs | Summary methods for Quantile Regression |
summary.rq | Summary methods for Quantile Regression |
summary.rqs | Summary methods for Quantile Regression |
summary.rqss | Summary of rqss fit |
table.rq | Table of Quantile Regression Results |
tau.nlrq | Function to compute nonlinear quantile regression estimates |
time.dynrq | Dynamic Linear Quantile Regression |
triogram.fidelity | Additive Nonparametric Terms for rqss Fitting |
triogram.penalty | Additive Nonparametric Terms for rqss Fitting |
uis | UIS Drug Treatment study data |
untangle.specials | Additive Quantile Regression Smoothing |
[.terms | Additive Quantile Regression Smoothing |