## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----------------------------------------------------------------------------- library(tsfgrnn) pred <- grnn_forecasting(UKgas, h = 4) pred$prediction ## ----fig.width=6-------------------------------------------------------------- plot(pred) ## ----fig.width=6-------------------------------------------------------------- library(ggplot2) autoplot(pred) ## ----------------------------------------------------------------------------- pred <- grnn_forecasting(timeS = 1:10, h = 2, lags = c(1, 3), msas = "MIMO", transform = "none") grnn_examples(pred) ## ----------------------------------------------------------------------------- grnn_weights(pred) ## ----------------------------------------------------------------------------- summary(pred) ## ----fig.width=6-------------------------------------------------------------- library(ggplot2) plot_example(pred, 1) ## ----fig.width=6-------------------------------------------------------------- plot_example(pred, 4) ## ----fig.width=6-------------------------------------------------------------- predr <- grnn_forecasting(1:10, h = 2, lags = c(1, 3), msas = "recursive", transform = "none") predr$prediction plot(predr) ## ----------------------------------------------------------------------------- grnn_examples(predr) ## ----fig.width=6-------------------------------------------------------------- ## ----fig.width=6-------------------------------------------------------------- plot_example(predr, position = 1, h = 1) ## ----------------------------------------------------------------------------- grnn_weights(predr)[[1]] ## ----fig.width=6-------------------------------------------------------------- plot_example(predr, position = 1, h = 2) ## ----------------------------------------------------------------------------- grnn_weights(predr)[[2]] ## ----------------------------------------------------------------------------- pred <- grnn_forecasting(ts(1:20), h = 4, lags = 1:2) ro <- rolling_origin(pred, h = 4) ## ----------------------------------------------------------------------------- print(ro$test_sets) ## ----------------------------------------------------------------------------- print(ro$predictions) ## ----------------------------------------------------------------------------- print(ro$errors) ## ----------------------------------------------------------------------------- ro$global_accu ## ----------------------------------------------------------------------------- ro$h_accu ## ----fig.width=6-------------------------------------------------------------- plot(ro, h = 4) ## ----------------------------------------------------------------------------- ro <- rolling_origin(pred, h = 4, rolling = FALSE) print(ro$test_sets) print(ro$predictions) ## ----fig.width=6-------------------------------------------------------------- pred <- grnn_forecasting(USAccDeaths, h = 12, lags = 1:12, sigma = 100) plot(pred) ## ----fig.width=6-------------------------------------------------------------- pred <- grnn_forecasting(USAccDeaths, h = 12, lags = 1:12, sigma = 0.05) plot(pred) ## ----------------------------------------------------------------------------- set.seed(5) timeS <- ts(1:10 + rnorm(10, 0, .2)) pred <- grnn_forecasting(timeS, h = 3, transform = "none") plot(pred) pred2 <- grnn_forecasting(timeS, h = 3, transform = "additive") plot(pred2)