Merge pull request #1 from Techtonique/vine-sim

Vine sim

.Rbuildignore

@@ -3,3 +3,6 @@
 ^ESGtoolkit\.Rcheck$
 ^ESGtoolkit.*\.tar\.gz$
 ^ESGtoolkit.*\.tgz$
+^_pkgdown\.yml$
+^docs$
+^pkgdown$

.gitignore

@@ -8,3 +8,4 @@ src/*.dll
 ESGtoolkit.Rcheck/
 ESGtoolkit*.tar.gz
 ESGtoolkit*.tgz
+docs

DESCRIPTION

@@ -1,23 +1,26 @@
 Package: ESGtoolkit
 Type: Package
 Title: Toolkit for Monte Carlo Simulations
-Version: 0.2.0
-Date: 2020-01-12
-Author: Thierry Moudiki
-Maintainer: Thierry Moudiki <thierry.moudiki@gmail.com>
+Version: 0.3.0
+Date: 2020-10-07
+Authors@R: c(
+        person("T.", "Moudiki", , "thierry.moudiki@gmail.com", role = c("aut", "cre")
+        )
+      )
+URL: https://techtonique.github.io/ESGtoolkit/
+BugReports: https://github.com/Techtonique/ESGtoolkit/issues
+Maintainer: T. Moudiki <thierry.moudiki@gmail.com>
 Description: A toolkit for Monte Carlo Simulations in Finance, Economics, Insurance, Physics. Multiple simulation models can be created by combining building blocks provided in the package.   
 License: BSD_3_clause Clear + file LICENSE
-Depends: CDVine, ggplot2, gridExtra, reshape2, ycinterextra
+Depends: ggplot2, gridExtra, reshape2, ycinterextra, VineCopula, randtoolbox
 Imports: Rcpp(>= 0.11.0)
 Suggests: 
-    knitr,
-    fOptions,
+    devtools,
     testthat
 LinkingTo: Rcpp
-VignetteBuilder: knitr
-Collate: 'RcppExports.R' 'fwdrates.R' 'plots.R' 'simulations.R' 'tests.R' 'tools.R'
+Collate: 'RcppExports.R' 'fwdrates.R' 'plots.R' 'simulations_risks.R' 'simulations_shocks.R' 'tests.R' 'tools.R' 'zzz.R'
 Packaged: 2014-06-12 23:32:30 UTC; Thierry
 NeedsCompilation: yes
 Repository: CRAN
 Date/Publication: 2014-06-13 06:17:14
-RoxygenNote: 7.0.2
+RoxygenNote: 7.1.1

ESGtoolkit.Rproj

@@ -15,4 +15,3 @@ LaTeX: pdfLaTeX
 BuildType: Package
 PackageInstallArgs: --no-multiarch --with-keep.source
 PackageCheckArgs: --as-cran
-PackageRoxygenize: rd,collate,namespace

NAMESPACE

@@ -12,8 +12,12 @@ export(simshocks)
 importFrom(ggplot2, ggplot)
 importFrom(ggplot2, qplot)
 importFrom(gridExtra, grid.arrange)
-importFrom(CDVine, CDVineSim)
+importFrom(randtoolbox, sobol)
+importFrom(randtoolbox, halton)
 importFrom(reshape2, melt)
+importFrom(VineCopula, C2RVine)
+importFrom(VineCopula, D2RVine)
+importFrom(VineCopula, RVineSim)
 importFrom(ycinterextra, ycinter)
 importFrom(ycinterextra, ycextra)
 importFrom(ycinterextra, fitted)

NEWS.md

@@ -0,0 +1,17 @@
+# version 0.3.0
+
+- Use [VineCopula](http://tnagler.github.io/VineCopula/) package instead of CDVine (archived) for dependency simulation (means there's also now VineCopula's R-Vine Copulas simulation)
+- Remove roxygen2 comments
+- Create website with pkgdown, including docs --> https://techtonique.github.io/ESGtoolkit/
+
+
+# version 0.2.0
+
+- refactor files 
+- add reproductibility seeds
+- update vignette
+- update LICENSE
+
+# version 0.1.0
+
+- Initial version

R/fwdrates.R

@@ -1,69 +1,7 @@
 # Instantaneous forward rates ---------------------------------------------
 
 
-#'@title 
-#'
-#'Instantaneous forward rates
-#'
-#'@description
-#'
-#'This function provides instantaneous forward rates. They can be used 
-#'in no-arbitrage short rate models, to fit the yield curve exactly. 
-#'
-#'@param in.maturities input maturities
-#'
-#'@param in.zerorates input zero rates
-#'
-#'@param n number of independent observations
-#'
-#'@param horizon horizon of projection
-#'
-#'@param out.frequency either "annual", "semi-annual", "quarterly", "monthly", 
-#'"weekly", or "daily" (1, 1/2, 1/4, 1/12, 1/52, 1/252)
-#'
-#'@param ... additional parameters provided to \code{\link{ycinter}}
-#'
-#'@author
-#'
-#'Thierry Moudiki
-#'
-#'@references
-#'
-#' Thierry Moudiki (2013). ycinterextra: Yield curve or zero-coupon prices interpolation and extrapolation. R package version 0.1. URL 
-#'\url{https://CRAN.R-project.org/package=ycinterextra}
-#'
-#'@examples
-#'
-#'# Yield to maturities
-#'txZC <- c(0.01422,0.01309,0.01380,0.01549,0.01747,0.01940,0.02104,0.02236,0.02348,
-#'          0.02446,0.02535,0.02614,0.02679,0.02727,0.02760,0.02779,0.02787,0.02786,0.02776
-#'          ,0.02762,0.02745,0.02727,0.02707,0.02686,0.02663,0.02640,0.02618,0.02597,0.02578,0.02563)
-#'
-#'# Observed maturities
-#'u <- 1:30
-#'
-#'\dontrun{
-#'par(mfrow=c(2,2))
-#'fwdNS <- esgfwdrates(in.maturities = u, in.zerorates = txZC, 
-#'                     n = 10, horizon = 20, 
-#'                     out.frequency = "semi-annual", method = "NS")
-#'matplot(time(fwdNS), fwdNS, type = 'l')
-#'
-#'fwdSV <- esgfwdrates(in.maturities = u, in.zerorates = txZC, 
-#'                     n = 10, horizon = 20, 
-#'                     out.frequency = "semi-annual", method = "SV")
-#'matplot(time(fwdSV), fwdSV, type = 'l')
-#'
-#'fwdSW <- esgfwdrates(in.maturities = u, in.zerorates = txZC, 
-#'                     n = 10, horizon = 20, 
-#'                     out.frequency = "semi-annual", method = "SW")
-#'matplot(time(fwdSW), fwdSW, type = 'l')
-#'
-#'fwdHCSPL <- esgfwdrates(in.maturities = u, in.zerorates = txZC, 
-#'                        n = 10, horizon = 20, 
-#'                        out.frequency = "semi-annual", method = "HCSPL")
-#'matplot(time(fwdHCSPL), fwdHCSPL, type = 'l')
-#'}
+# Instantaneous forward rates
 esgfwdrates <- function(in.maturities, in.zerorates,
                         n, horizon, 
                         out.frequency = c("annual", "semi-annual", 
@@ -124,5 +62,4 @@ esgfwdrates <- function(in.maturities, in.zerorates,
 
   return(ts(replicate(n, fwdrates), start = 0,
             deltat = delta))
-}
-esgfwdrates <- cmpfun(esgfwdrates)
+}

R/plots.R

@@ -2,75 +2,7 @@
 # Misc plots --------------------------------------------------------------
 
 
-#'@title Plot time series percentiles and confidence intervals
-#'
-#'@description
-#'
-#'This function plots colored bands for time series percentiles and confidence 
-#'intervals. You can use it for outputs from \code{link{simdiff}}, 
-#'\code{link{esgmartingaletest}}, \code{link{esgcortest}}.
-#'
-#'@param x a times series object 
-#'
-#'@param ... additionnal (optional) parameters provided to \code{plot}
-#'
-#'@export
-#'
-#'@author Thierry Moudiki
-#'
-#'@seealso \code{\link{esgplotts}}
-#'
-#'@examples
-#'
-#'# Times series
-#'
-#'kappa <- 1.5
-#'V0 <- theta <- 0.04
-#'sigma <- 0.2
-#'theta1 <- kappa*theta
-#'theta2 <- kappa
-#'theta3 <- sigma
-#'x <- simdiff(n = 100, horizon = 5, 
-#'frequency = "quart",  
-#'model = "OU", 
-#'x0 = V0, theta1 = theta1, theta2 = theta2, theta3 = theta3)
-#'
-#'par(mfrow=c(2,1))
-#'esgplotbands(x, xlab = "time", ylab = "values")
-#'matplot(time(x), x, type = 'l', xlab = "time", ylab = "series values")
-#'
-#'# Martingale test
-#'
-#'r0 <- 0.03
-#'S0 <- 100
-#'sigma0 <- 0.1
-#'nbScenarios <- 100
-#'horizon0 <- 10
-#'eps0 <- simshocks(n = nbScenarios, horizon = horizon0, frequency = "quart",
-#' method = "anti")
-#'sim.GBM <- simdiff(n = nbScenarios, horizon = horizon0, frequency = "quart",   
-#'                  model = "GBM", 
-#'                  x0 = S0, theta1 = r0, theta2 = sigma0, 
-#'                  eps = eps0)
-#'
-#'mc.test <- esgmartingaletest(r = r0, X = sim.GBM, p0 = S0, alpha = 0.05)   
-#'esgplotbands(mc.test)
-#'
-#'# Correlation test
-#'
-#'nb <- 500
-#'
-#'s0.par1 <- simshocks(n = nb, horizon = 3, frequency = "semi",
-#'family = 1, par = 0.2)
-#'
-#'s0.par2 <- simshocks(n = nb, horizon = 3, frequency = "semi", 
-#'family = 1, par = 0.8)
-#'
-#'(test1 <- esgcortest(s0.par1))
-#'(test2 <- esgcortest(s0.par2))
-#'par(mfrow=c(2, 1))
-#'esgplotbands(test1)
-#'esgplotbands(test2)
+# Plot time series percentiles and confidence intervals
 esgplotbands <- function(x, ...)
 {
   if (is.ts(x))
@@ -143,7 +75,7 @@ esgplotbands <- function(x, ...)
       abs <- as.numeric(time(x$conf.int))
       y.mean <- rep(0, length(abs))
 
-      par(mfrow = c(2, 1))
+      par(mfrow = c(1, 2))
       bands.plot(abs, y.mean, ci.upper = x$conf.int[, 2], ci.lower =  x$conf.int[, 1], 
                  col = "gray80", ylim = c(min(x$conf.int[, 1]), max(x$conf.int[, 2])), 
                  xlab = "time", ylab = "conf. int.", 
@@ -162,42 +94,7 @@ esgplotbands <- function(x, ...)
 }
 
 
-
-#'@title Plot time series objects
-#'
-#'@description This function plots outputs from \code{\link{simdiff}}.
-#'
-#'@details For a large number of simulations, it's preferable to use 
-#'\code{\link{esgplotbands}} for a synthetic view by percentiles.
-#'
-#'@param x a time series object, an output from \code{\link{simdiff}}.
-#'
-#'@seealso \code{\link{simdiff}}, \code{\link{esgplotbands}}
-#'
-#'@author
-#'
-#'Thierry Moudiki
-#'
-#'@export
-#'
-#'@references
-#'
-#'H. Wickham (2009), ggplot2: elegant graphics for data analysis. Springer 
-#'New York.
-#'
-#'@examples
-#'kappa <- 1.5
-#'V0 <- theta <- 0.04
-#'sigma <- 0.2
-#'theta1 <- kappa*theta
-#'theta2 <- kappa
-#'theta3 <- sigma
-#'x <- simdiff(n = 10, horizon = 5, frequency = "quart",  
-#'model = "OU", 
-#'x0 = V0, theta1 = theta1, theta2 = theta2, theta3 = theta3)
-#'
-#'esgplotts(x)
-#'
+# Plot time series objects
 esgplotts <- function(x)
 { 
   x0 <- start(x)[1]
@@ -209,77 +106,9 @@ esgplotts <- function(x)
     xlab("Maturity") + ylab("Values") + 
     ggplot2::theme(legend.position = "none")
 }
-esgplotts <- cmpfun(esgplotts)
-
 
 
-#'@title Visualize the dependence between 2 gaussian shocks
-#'
-#'@description
-#'
-#'This function helps you in visualizing the dependence between 2 gaussian
-#' shocks. 
-#'
-#'@param x an output from \code{\link{simshocks}}, a list with 2 components.
-#'
-#'@param y an output from \code{\link{simshocks}}, a list with 2 components 
-#'(Optional). 
-#'
-#'@export
-#'
-#'@seealso \code{\link{simshocks}}
-#'
-#'@author Thierry Moudiki + some nice blogs :) 
-#'
-#'@references
-#'
-#'H. Wickham (2009), ggplot2: elegant graphics for data analysis. Springer 
-#'New York.
-#'
-#'@examples
-#'
-#'# Number of risk factors
-#'d <- 2
-#'
-#'# Number of possible combinations of the risk factors
-#'dd <- d*(d-1)/2
-#'
-#'# Family : Gaussian copula 
-#'fam1 <- rep(1,dd)
-#'# Correlation coefficients between the risk factors (d*(d-1)/2)
-#'par0.1 <- 0.1
-#'par0.2 <- -0.9
-#'
-#'# Family : Rotated Clayton (180 degrees)
-#'fam2 <- 13
-#'par0.3 <- 2
-#'
-#'# Family : Rotated Clayton (90 degrees)
-#'fam3 <- 23
-#'par0.4 <- -2
-#'
-#'# number of simulations
-#'nb <- 500
-#'
-#'# Simulation of shocks for the d risk factors
-#'s0.par1 <- simshocks(n = nb, horizon = 4, 
-#'family = fam1, par = par0.1)
-#'
-#'s0.par2 <- simshocks(n = nb, horizon = 4, 
-#'family = fam1, par = par0.2)
-#'
-#'s0.par3 <- simshocks(n = nb, horizon = 4, 
-#'family = fam2, par = par0.3)
-#'
-#'s0.par4 <- simshocks(n = nb, horizon = 4, 
-#'family = fam3, par = par0.4)
-#'
-#'\dontrun{
-#'esgplotshocks(s0.par1, s0.par2)
-#'esgplotshocks(s0.par2, s0.par3)
-#'esgplotshocks(s0.par2, s0.par4)
-#'esgplotshocks(s0.par1, s0.par4)} 
-#'
+# Visualize the dependence between 2 gaussian shocks
 esgplotshocks <-  function(x, y = NULL)
 {
   x <- matrix(unlist(x), ncol = 2)
@@ -338,6 +167,4 @@ esgplotshocks <-  function(x, y = NULL)
 
   #arrange the plots together, with appropriate height and width for each row and column
   grid.arrange(plot_top, empty, scatter, plot_right, ncol=2, nrow=2, widths=c(4, 1), heights=c(1, 4))
-}
-esgplotshocks  <- cmpfun(esgplotshocks)
-
+}