| .normalise | Normalise a vector |
| add_term | Stepwise model construction and inspection |
| as_complex | Coerce to complex |
| as_complex-method | Coerce to complex |
| avoid | Avoid overlaps |
| avoid-method | Avoid overlaps |
| bc | Box-Cox transform |
| bc_inv | Box-Cox transform inverse |
| Boston | Boston |
| box_cox | Box-cox constructor function |
| box_cox-method | Box-cox constructor function |
| Cars93 | Cars93 |
| cm2in | Unit change functions |
| default_test | Guess the default test |
| default_test.default | Guess the default test |
| default_test.glm | Guess the default test |
| default_test.glmerMod | Guess the default test |
| default_test.lm | Guess the default test |
| default_test.lmerMod | Guess the default test |
| default_test.multinom | Guess the default test |
| default_test.negbin | Guess the default test |
| default_test.polr | Guess the default test |
| drop_term | Stepwise model construction and inspection |
| eigen2 | Generalized eigenvalue problem |
| GIC | Intermediate Information Criterion |
| givens_orth | Givens orthogonalisation |
| gs_orth | Gram-Schmidt orthogonalization |
| gs_orth_modified | Gram-Schmidt orthogonalization |
| hr_levels | #' @rdname kde_1d #' @export kernelBiweight <- function(x, mean = 0, sd = 1) h <- sqrt(7)*sd ifelse((z <- abs(x-mean)) < h, 15/16*(1 - (z/h)^2)^2/h, 0) |
| hr_levels.default | #' @rdname kde_1d #' @export kernelBiweight <- function(x, mean = 0, sd = 1) h <- sqrt(7)*sd ifelse((z <- abs(x-mean)) < h, 15/16*(1 - (z/h)^2)^2/h, 0) |
| hr_levels.kde_2d | #' @rdname kde_1d #' @export kernelBiweight <- function(x, mean = 0, sd = 1) h <- sqrt(7)*sd ifelse((z <- abs(x-mean)) < h, 15/16*(1 - (z/h)^2)^2/h, 0) |
| in2cm | Unit change functions |
| in2mm | Unit change functions |
| in2usr | Conversion functions for plotting |
| in2usr-method | Conversion functions for plotting |
| kde_1d | One-dimensional Kernel Density Estimate |
| kde_2d | A Two-dimensional Kernel Density Estimate |
| lambda | Find the box-cox transform exponent estimate |
| lambda.box_cox | Find the box-cox transform exponent estimate |
| lambda.default | Find the box-cox transform exponent estimate |
| lambda.formula | Find the box-cox transform exponent estimate |
| lambda.lm | Find the box-cox transform exponent estimate |
| makepredictcall.normalise | Method function for safe prediction |
| mean_c | Mean and variance for a circular sample |
| mm2in | Unit change functions |
| plot.box_cox | Box-cox constructor function |
| plot.drop_term | drop_term plot method |
| plot.kde_1d | One-dimensional Kernel Density Estimate |
| plot.kde_2d | A Two-dimensional Kernel Density Estimate |
| print.box_cox | Box-cox constructor function |
| print.kde_1d | One-dimensional Kernel Density Estimate |
| print.kde_2d | A Two-dimensional Kernel Density Estimate |
| print.lambda | Print method for Box-Cox objects |
| quine | quine |
| step_AIC | Stepwise model construction and inspection |
| step_BIC | Stepwise model construction and inspection |
| step_down | Naive backeward elimination |
| step_GIC | Stepwise model construction and inspection |
| unitChange | Unit change functions |
| usr2in | Conversion functions for plotting |
| usr2in-method | Conversion functions for plotting |
| var_c | Mean and variance for a circular sample |
| vcovx | Extended variance matrix |
| vcovx.default | Extended variance matrix |
| vcovx.negbin | Extended variance matrix |
| which_tri | Which in lower/upper triangle |
| whiteside | whiteside |
| xy-class | An S4 class to represent alternavive complex, matrix or list input forms. |
| zq | Standardisation functions for models |
| zr | Standardisation functions for models |
| zs | Standardisation functions for models |
| zu | Standardisation functions for models |