R/RcppExports.R

In 3schwartz/SpecialeScrAndFun: Script and functions used for master thesis.

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

#' @title clayton_theta_cpp
#' @description
#' Get next dependence parameter
#' @name clayton_theta_cpp
#' @param par Vector of length three wiht parameters w, alpha and beta
#' @param double theta_{t-1}
#' @param matrix 2-dimensinal matrix with U(1)-margins values
#'
#' @export
NULL

clayton_theta_cpp <- function(par, th_old, U) {
    .Call('_scrAndFun_clayton_theta_cpp', PACKAGE = 'scrAndFun', par, th_old, U)
}

#' @title corrRollMatrixCpp
#' @description
#' Calculate rolling correlation between each column in input matrix
#' @name corrRollMatrixCpp
#' @param X a matrix of which one want to calculate correlation of between each asset
#' @param period number one want to use when taking rolling correlation
#'
#' @export
corrRollMatrixCpp <- function(X, period) {
    .Call('_scrAndFun_corrRollMatrixCpp', PACKAGE = 'scrAndFun', X, period)
}

#' @title ExpWeiAvgReCpp
#' @description
#' Returns exponentially weighted average return
#' @name ExpWeiAvgReCpp
#' @param r a numeric vector
#' @param delta size of weight
#' @param annu number of days to get data annualized
#'
#' @export
NULL

ExpWeiAvgReCpp <- function(r, delta, annu) {
    .Call('_scrAndFun_ExpWeiAvgReCpp', PACKAGE = 'scrAndFun', r, delta, annu)
}

#' @title ExpWeiVarCpp
#' @description
#' Returns exponentially weighted varaince
#' @name ExpWeiVarCpp
#' @param r a numeric vector
#' @param delta size of weight
#' @param annu number of days to get data annualized
#'
#' @export
NULL

ExpWeiVarCpp <- function(r, delta, annu) {
    .Call('_scrAndFun_ExpWeiVarCpp', PACKAGE = 'scrAndFun', r, delta, annu)
}

#' @title LL_clayton_cpp
#' @description
#' Get minus loglikelihood of time varying Clayton cpula
#' @name LL_clayton_cpp
#' @param par Vector of length three wiht parameters w, alpha and beta
#' @param 2-dimensinal matrix with U(0,1)-margins values
#'
#' @export
NULL

LL_clayton_cpp <- function(par, U) {
    .Call('_scrAndFun_LL_clayton_cpp', PACKAGE = 'scrAndFun', par, U)
}

#' @title LL_clayton_cpp_v2
#' @description
#' Get minus loglikelihood of time varying Clayton cpula
#' @name LL_clayton_cpp_v2
#' @param par Vector of length three wiht parameters w, alpha and beta
#' @param 2-dimensinal matrix with U(0,1)-margins values
#'
#' @export
NULL

LL_clayton_cpp_v2 <- function(par, U) {
    .Call('_scrAndFun_LL_clayton_cpp_v2', PACKAGE = 'scrAndFun', par, U)
}

#' @title LL_clayton_sim_cpp
#' @description
#' Simulation of time varying Clayton cpula
#' @name LL_clayton_sim_cpp
#' @param par Vector of length three wiht parameters w, alpha and beta
#' @param 2-dimensinal matrix with U(0,1)-margins values
#'
#' @export
NULL

LL_clayton_sim_cpp <- function(par, U) {
    .Call('_scrAndFun_LL_clayton_sim_cpp', PACKAGE = 'scrAndFun', par, U)
}

#' @title LL_clayton_static_cpp
#' @description
#' Get minus loglikelihood of Clayton cpula
#' @name LL_clayton_static_cpp
#' @param th scalar with theta
#' @param U 2-dimensinal matrix with U(0,1)-margins values
#'
#' @export
NULL

LL_clayton_static_cpp <- function(th, U) {
    .Call('_scrAndFun_LL_clayton_static_cpp', PACKAGE = 'scrAndFun', th, U)
}

#' @title LL_clayton_surv_cpp
#' @description
#' Get minus loglikelihood of time varying Clayton cpula
#' @name LL_clayton_surv_cpp
#' @param par Vector of length three wiht parameters w, alpha and beta
#' @param 2-dimensinal matrix with U(0,1)-margins values
#'
#' @export
NULL

LL_clayton_surv_cpp <- function(par, U) {
    .Call('_scrAndFun_LL_clayton_surv_cpp', PACKAGE = 'scrAndFun', par, U)
}

#' @title LL_clayton_surv_sim_cpp
#' @description
#' Get minus loglikelihood of time varying Clayton cpula
#' @name LL_clayton_surv_sim_cpp
#' @param par Vector of length three wiht parameters w, alpha and beta
#' @param 2-dimensinal matrix with U(0,1)-margins values
#'
#' @export
NULL

LL_clayton_surv_sim_cpp <- function(par, U) {
    .Call('_scrAndFun_LL_clayton_surv_sim_cpp', PACKAGE = 'scrAndFun', par, U)
}

#' @title LL_gaus_cpp
#' @description
#' Get minus loglikelihood of time varying Gaussian copula, using updating from Patton 2006a
#' @name LL_gaus_cpp
#' @param par Vector of length three wiht parameters w, alpha and beta
#' @param 2-dimensinal matrix with U(0,1)-margins values
#' @param Number used in weighted sum
#'
#' @export
NULL

LL_gaus_cpp <- function(par, U, M) {
    .Call('_scrAndFun_LL_gaus_cpp', PACKAGE = 'scrAndFun', par, U, M)
}

#' @title LL_gaus_sim_cpp
#' @description
#' Simulation of time varying Gaussian copula, using updating from Patton 2006a
#' @name LL_gaus_sim_cpp
#' @param par Vector of length three wiht parameters w, alpha and beta
#' @param 2-dimensinal matrix with U(0,1)-margins values
#' @param Number used in weighted sum
#'
#' @export
NULL

LL_gaus_sim_cpp <- function(par, U, M) {
    .Call('_scrAndFun_LL_gaus_sim_cpp', PACKAGE = 'scrAndFun', par, U, M)
}

#' Multiply a number by two
#'
#' @param x A single integer.
#' @export
timesTwo <- function(x) {
    .Call('_scrAndFun_timesTwo', PACKAGE = 'scrAndFun', x)
}