tsfgrnn.R
In tsfgrnn: Time Series Forecasting Using GRNN

## ---- 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)

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grnn_weights(pred)

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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)

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grnn_weights(predr)[[1]]

## ---- fig.width=6-------------------------------------------------------------
plot_example(predr, position = 1, h = 2)

## -----------------------------------------------------------------------------
grnn_weights(predr)[[2]]

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pred <- grnn_forecasting(ts(1:20), h = 4, lags = 1:2)
ro <- rolling_origin(pred, h = 4)

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print(ro$test_sets)

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print(ro$predictions)

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print(ro$errors)

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ro$global_accu

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ro$h_accu

## ---- fig.width=6-------------------------------------------------------------
plot(ro, h = 4)

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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)