GPCA_iteration: This function makes an iteration of PCA-Gaussianization... In RMAWGEN: Multi-Site Auto-Regressive Weather GENerator

Description

This function makes an iteration of PCA-Gaussianization process

Usage

 `1` ```GPCA_iteration(x_prev, extremes = TRUE) ```

Arguments

 `x_prev` previous set of random variable `x` `extremes` see `normalizeGaussian_severalstations`

Value

A `GPCA_iteration` S3 object which contains the following objects:

`x_prev` Previous set of random variable, `x_prev` input variable

`x_gauss_prev` Marginal Gaussianization of `x_prev` obtained through `normalizeGaussian_severalstations`

`B_prev` rotation matrix (i. e. eigenvector matrix of the covariance matrix of `x_gauss_prev`

`x_next` results obtained by multiplying `B_prev` by `x_gauss_prev` (see equation 1 of the reference)

Note

This function is based on equation (1) of "PCA Gaussianization for One-Class Remote Sensing Image" by V. Laparra et al., www.uv.es/lapeva/papers/SPIE09_one_class.pdf and http://ieeexplore.ieee.org/document/5413808/

Author(s)

Emanuele Cordano

`GPCA`,`GPCA_iteration`,`inv_GPCA_iteration`,`inv_GPCA`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```library(RMAWGEN) set.seed(1222) N <- 20 x <- rexp(N) y <- x+rnorm(N) df <- data.frame(x=x,y=y) GPCA <- GPCA_iteration(df,extremes=TRUE) x <- rnorm(N) y <- x+rnorm(N) dfn <- data.frame(x=x,y=y) GPCAn <- GPCA_iteration(dfn,extremes=TRUE) ```