canbw | does the canonical bandwith transformation of a bandwith value of kernel K1 into an equivalent bandwidth for Kernel K2. |
canker | does the canonical bandwith transformation of a bandwith value of kernel K1 into an equivalent bandwidth for Kernel K2. |
denbwcrit | determines the optimal from a range of bandwidths by one of the following bandwidth selection criteria: Least Squares Cross Validation (lscv), Biased Cross Validation (bcv), Smoothed Cross Validation (scv), Jones, Marron and Park Cross Validation (jmp), Park and Marron Plug-in (pm), Sheather and Jones Plug-in (sj), and Silverman's rule of thumb. |
denbwsel | interactive tool for bandwidth selection in univariate kernel density estimation. |
dencb | computes uniform confidence bands with prespecified confidence level for univariate density estimation. |
denci | computes pointwise confidence intervals with prespecified confidence level for univariate density estimation. The computation uses WARPing. |
denest | estimates a univariate density by kernel density estimation. The computation uses WARPing. |
denestp | estimates a p-dimensional density by kernel density estimation. The computation uses WARPing. |
denrot | determines a rule-of-thumb bandwidth for univariate density estimation according to Silverman. |
denrotp | determines a rule-of-thumb bandwidth for multivariate density estimation according to Scott. |
denxcb | computes uniform confidence bands with prespecified confidence level for univariate density estimation. |
denxci | computes pointwise confidence intervals with prespecified confidence level for univariate density estimation. |
denxest | estimates a univariate density by kernel density estimation. |
denxestp | estimates a p-dimensional density by kernel density estimation. The computation uses WARPing. |
gauder | gauder evaluates derivatives of the Gaussian kernel rescaled by a bandwidth h, to be used for density estimation bandwidth selection. |
looreg | computes the Nadaraya-Watson leave-one-out estimator without binning using the quartic kernel. Prior to estimation, looreg sorts the data. The sorted data, along with the sorted leave-one-out regression estimates, are returned as an output. |
lpderest | estimates the q-th derivative of a regression function using local polynomial kernel regression. The computation uses WARPing. |
lpderrot | determines a rule-of-thumb bandwidth for univariate local polynomial derivatives estimation using the Quartic kernel. |
lpderxest | estimates the q-th derivative of a regression function using local polynomial kernel regression with Quartic kernel. |
lpregest | estimates a regression function using local polynomial kernel regression. The computation uses WARPing. |
lpregrot | determines a rule-of-thumb bandwidth for univariate local polynomial kernel regression using the Quartic kernel. |
lpregxest | estimates a univariate regression function using local polynomial kernel regression with Quartic kernel. |
lprotint | lprotint computes the integral of the (p+1)st derivative of a polynomial of order (p+3), this function is used to find rule-of-thumb bandwidth for local polynomial regression and derivative estimation |
lregestp | estimates a multivariate regression function using local polynomial kernel regression. The computation uses WARPing. |
lregxestp | estimates a multivariate regression function using local polynomial kernel regression with Quartic kernel. |
lvtest | This quantlet tests for significance of a subset or of the whole set of continuous regresssors in a nonparametric regression. |
regbwcrit | determines the optimal from a range of bandwidths by one using the resubstitution estimator with one of the following penalty functions: Shibata's penalty function (shi), Generalized Cross Validation (gcv), Akaike's Information Criterion (aic), Finite Prediction Error (fpe), Rice's T function (rice). The computation uses WARPing. |
regbwsel | interactive tool for bandwidth selection in univariate kernel regression estimation. |
regcb | computes uniform confidence bands with prespecified confidence level for univariate regression using the Nadaraya-Watson estimator. The computation uses WARPing. |
regci | computes pointwise confidence intervals with prespecified confidence level for univariate regression using the Nadaraya-Watson estimator. The computation uses WARPing. |
regest | computes the Nadaraya-Watson estimator for univariate regression. The computation uses WARPing. |
regestp | Nadaraya-Watson estimator for multivariate regression. The computation uses WARPing. |
regxbwcrit | determines the optimal from a range of bandwidths by one using the resubstitution estimator with one of the following penalty functions: Shibata's penalty function (shi), Generalized Cross Validation (gcv), Akaike's Information Criterion (aic), Finite Prediction Error (fpe), Rice's T function (rice). |
regxbwsel | interactive tool for bandwidth selection in univariate kernel regression estimation. |
regxcb | computes uniform confidence bands with prespecified confidence level for univariate regression using the Nadaraya-Watson estimator. |
regxci | computes pointwise confidence intervals with prespecified confidence level for univariate regression using the Nadaraya-Watson estimator. |
regxest | computes the Nadaraya-Watson estimator for univariate regression. |
regxestp | computes the Nadaraya-Watson estimator for multivariate regression. |
smoothermain | loads the kernels needed by the smoother lib functions |
smoothertest | smoothertest tests all the aforementioned macros of the smoother.lib |
spfill | spfill fills places of sparsity with interpolated observations to avoid the need of oversmoothing. |
supsmo | calculates the super smoother |