plot_ts_pred: Plot a time series chart

In daltoolbox: Leveraging Experiment Lines to Data Analytics

Plot a time series chart

Description

The function receives six variables as a parameter, which are obj and y, yadj, main and xlabels. The graph is plotted with 3 lines: the original series (in black), the adjusted series (in blue) and the predicted series (in green)

Usage

plot_ts_pred(
  x = NULL,
  y,
  yadj,
  ypred = NULL,
  label_x = "",
  label_y = "",
  color = "black",
  color_adjust = "blue",
  color_prediction = "green"
)

Arguments

x	time index
y	time series
yadj	adjustment of time series
ypred	prediction of the time series
label_x	x-axis title
label_y	y-axis title
color	color for the time series
color_adjust	color for the adjusted values
color_prediction	color for the predictions

Value

ggplot graphic

Examples

data(sin_data)
ts <- ts_data(sin_data$y, 0)
ts_head(ts, 3)


samp <- ts_sample(ts, test_size= 5)
io_train <- ts_projection(samp$train)
io_test <- ts_projection(samp$test)

model <- ts_arima()
model <- fit(model, x=io_train$input, y=io_train$output)
adjust <- predict(model, io_train$input)

prediction <- predict(model, x=io_test$input, steps_ahead=5)
prediction <- as.vector(prediction)

yvalues <- c(io_train$output, io_test$output)
grf <- plot_ts_pred(y=yvalues, yadj=adjust, ypre=prediction)
plot(grf)

daltoolbox documentation built on May 29, 2024, 1:57 a.m.