Package index • Qtools

All functions

Chemistry: A-level Chemistry Scores
KhmaladzeFormat(): Khmaladze Test
LOFTest(): Lack-of-Fit Tests for Quantile Regression Models
Orthodont: Growth curve data on an orthdontic measurement
Qtools-package: Utilities for Quantilies
ao() invao() bc() invbc() mcjI() invmcjI() mcjII() invmcjII(): Transformations
cmidecdf() cmidecdf.fit(): Mid-distribution Functions
coef(<midrq>) coefficients(<midrq>): Extract Coefficients
coef(<qrr>) coefficients(<qrr>): Extract Coefficients
coef(<rq.counts>) coefficients(<rq.counts>): Extract Coefficients
coef(<rqt>) coefficients(<rqt>): Extract Coefficients
confint(<midquantile>): Mid-distribution Functions
dqc() dqc.fit(): Directional Quantile Classification
dqcControl(): Control parameters for dqc estimation
esterase: Esterase Essay Data
fars: FARS Data
fitted(<midrq>): Extract Fitted Values from Mid-Quantile Transformation Models
fitted(<rq.counts>): Extract Fitted Values from Quantile Regression Models for Counts
fitted(<rqt>): Extract Fitted Values from Quantile Regression Transformation Models
labor: Labor Pain Data
maref(): Marginal Effects
mice.impute.rq() mice.impute.rrq(): QR-based Multiple Imputation
midq2q(<midquantile>) midq2q(<midrq>): Recover Ordinary Quantiles from Mid-Quantiles
midecdf() midquantile(): Mid-distribution Functions
midrq() midrq.fit(): Mid-Quantile Regression for Discrete Responses
midrqControl(): Control parameters for midrq estimation
nlControl(): Control parameters for gradient search estimation
plot(<midq2q>): Plot Quantile Functions
plot(<midecdf>) plot(<midquantile>): Plot Mid-distribution Functions
plot(<qlss>): Quantile-based Summary Statistics for Location, Scale and Shape
predict(<midrq>): Predictions from Mid-Quantile Regression Models
predict(<qlss>): Predictions from Conditional LSS Objects
predict(<qrr>): Predictions from Quantile Ratio Regression Models
predict(<rq.counts>): Predictions from rq.counts Objects
predict(<rqt>): Predictions from Quantile Regression Transformation Models
predict(<rrq>): Predictions from Restricted Quantile Regression Models
print(<LOFTest>): Print Lack-of-Fit Test for Quantile Regression Models
print(<cmidecdf>): Print Mid-distribution Functions
print(<dqc>): Print Directional Quantile Classification Objects
print(<midecdf>) print(<midquantile>): Print Mid-distribution Functions
print(<midrq>) print(<summary.midrq>): Print Mid-Quantile Models
print(<qlss>): Print Quantile-based Summary Statistics for Location, Scale and Shape
print(<qrr>) print(<summary.qrr>): Print Quantile Ratio Regression Models
print(<rq.counts>): Print rq.counts
print(<rqt>) print(<summary.rqt>): Print Transformation Models
print(<rrq>) print(<summary.rrq>): Print Restricted Quantile Regression Models
qexact(): Exact Confidence Intervals for Quantiles
qlss(): Quantile-based Summary Statistics for Location, Scale and Shape
qrr(): Quantile Ratio Regression
qsmspline(): Quantile Regression with Smoothing Splines
residuals(<midrq>): Residuals from a midrq Objects
residuals(<rq.counts>): Residuals from an rq.counts Object
residuals(<rqt>): Residuals from an rqt Objects
rq.counts(): Quantile Regression for Counts
rrq() rrq.fit() rrq.wfit(): Restricted Regression Quantiles
sparsity(): Sparsity Estimation
summary(<midrq>): Summary for Mid-Quantile Regression Models
summary(<qrr>): Summary for Quantile Ratio Regression Models
summary(<rqt>): Summary for Quantile Regression Tranformation Models
summary(<rrq>): Summary for Restricted Quantile Regression Models
tsrq() tsrq2() rcrq() nlrq1() nlrq2(): Quantile Regression Transformation Models
vcov(<midrq>): Variance-Covariance Matrix for a Fitted Mid-Quantile Regression Model Object
vcov(<qrr>): Variance-Covariance Matrix for a Fitted Quantile Ratio Regression Model Object