| binning | Data Binning |
| binning.default | Data Binning |
| binning.histogram | Data Binning |
| bootkde | Density estimation for data with rounding errors |
| bootPRO | Effectiveness Evaluation based on PROs with bootstrapping method |
| bootsmooth | non-parametric regression |
| bw.blscv | Compute a Binned Kernel Density Estimate for Weighted Data |
| bw.wnrd | Compute a Binned Kernel Density Estimate for Weighted Data |
| bw.wnrd0 | Compute a Binned Kernel Density Estimate for Weighted Data |
| ddeg | Fitting log-normal distributions |
| dGBP | Fitting Mixture Model of Generalized Beta and Pareto |
| dmlnorm | The mixed lognormal distribution |
| dmnorm | The mixed normal distribution |
| dPareto | The Pareto distribution |
| Employment2 | Firm size data |
| EUFirmSize | Firm size data of 10 EU countries |
| Firm2 | Firm size data |
| FirmAge | Firm size data |
| FirmDeathAge | Firm size data |
| FirmDeathSize | Firm size data |
| FirmEmploymentAge | Firm size data |
| FirmEmploymentSize | Firm size data |
| FirmJobAge | Firm size data |
| FirmJobSize | Firm size data |
| FirmSize | Firm size data |
| fit.Copula | Fitting firm size-age distributions |
| fit.FSD | Fitting firm size-age distributions |
| fit.GBP | Fitting Mixture Model of Generalized Beta and Pareto |
| fit.GLD | Fitting firm size-age distributions |
| fit.lnorm | Fitting log-normal distributions |
| fit.lognormal | Fitting log-normal distributions |
| fit.mlnorm | Fitting log-normal distributions |
| fit.Pareto | Fit a Pareto Distribution to Binned Data |
| fnm | Distribution of Two Finite Gaussian Mixtures |
| FSD | Firm size data |
| ImportFSD | Import Firm Size and Firm Age Data |
| Job2 | Firm size data |
| LCL | Breast Cancer Data |
| lines.FSD | Fitting firm size-age distributions |
| lines.VAS | Algorithms for Visual Analogue Scales |
| lps.variance | compute the variance of the local polynomial regression function |
| lpsmooth | non-parametric regression |
| mediation.test | The Sobel mediation test |
| meta | Breast Cancer Data |
| mixlognormal | Fitting log-normal distributions |
| NGS.normalize | Fitting log-normal distributions |
| normal | Breast Cancer Data |
| npr | non-parametric regression |
| ofc | occipitofrontal head circumference data |
| Pain | Pain data |
| pain | Pain data |
| pGBP | Fitting Mixture Model of Generalized Beta and Pareto |
| plot.bdata | Data Binning |
| plot.FSD | Fitting firm size-age distributions |
| plot.VAS | Algorithms for Visual Analogue Scales |
| pmixPU | The Pareto distribution |
| pmlnorm | The mixed lognormal distribution |
| pmnorm | The mixed normal distribution |
| pPareto | The Pareto distribution |
| primary | Breast Cancer Data |
| print.bdata | Data Binning |
| print.FSD | Fitting firm size-age distributions |
| print.mixlognormal | Fitting log-normal distributions |
| print.scb | non-parametric regression |
| print.VAS | Algorithms for Visual Analogue Scales |
| pro.test | Test effectiveness based on PROs |
| qmixPU | The Pareto distribution |
| qmlnorm | The mixed lognormal distribution |
| qmnorm | The mixed normal distribution |
| qPareto | The Pareto distribution |
| rmlnorm | The mixed lognormal distribution |
| rmnorm | The mixed normal distribution |
| rPareto | The Pareto distribution |
| tkde | Distribution of Two Finite Gaussian Mixtures |
| VAS.ecdf | Algorithms for Visual Analogue Scales |
| VAS.npr | Algorithms for Visual Analogue Scales |
| VAS.pdf | Algorithms for Visual Analogue Scales |
| wdekde | Algorithms for Visual Analogue Scales |
| wkde | Compute a Binned Kernel Density Estimate for Weighted Data |
| wlpsmooth | non-parametric regression |
| Zipf.Normalize | Zipf Normalization |
| ZipfPlot | Draw Zipf Plot |
| ZipfPlot.bdata | Draw Zipf Plot |
| ZipfPlot.default | Draw Zipf Plot |
| ZipfPlot.FSD | Draw Zipf Plot |
| ZipfPlot.histogram | Draw Zipf Plot |