Title: | Time Series Forecast System |
---|---|
Description: | A web application for displaying, analysing and forecasting univariate time series. Includes basic methods such as mean, naïve, seasonal naïve and drift, as well as more complex methods such as Holt-Winters Box,G and Jenkins, G (1976) <doi:10.1111/jtsa.12194> and ARIMA Brockwell, P.J. and R.A.Davis (1991) <doi:10.1007/978-1-4419-0320-4>. |
Authors: | Oldemar Rodriguez [aut, cre], Diego Jiménez [aut] |
Maintainer: | Oldemar Rodriguez <[email protected]> |
License: | GPL (>= 2) |
Version: | 3.0.2 |
Built: | 2024-11-26 11:44:25 UTC |
Source: | CRAN |
Best parameters arima model
calibrar.arima(train, test, period, ar = 0:2, es = 0:1)
calibrar.arima(train, test, period, ar = 0:2, es = 0:1)
train |
a ts object (train of a time series). |
test |
a ts object (test of a time series). |
period |
value indicate the period to use. |
ar |
vector of values to test p, d, q of arima model. |
es |
vector of values to test P, D, Q of arima model. |
arima model
Diego Jimenez <[email protected]>
calibrar.arima(AirPassengers[1:132], AirPassengers[133:144], 12, 0:1)
calibrar.arima(AirPassengers[1:132], AirPassengers[133:144], 12, 0:1)
Best parameters HoltWinters model
calibrar.HW(train, test, paso = 0.1)
calibrar.HW(train, test, paso = 0.1)
train |
a ts object (train of a time series). |
test |
a ts object (test of a time series). |
paso |
indicates by value to test alpha, beta and gamma. |
HoltWinters model
Diego Jimenez <[email protected]>
calibrar.HW(window(AirPassengers, end = c(1959, 12)), window(AirPassengers, start = 1960), 0.5)
calibrar.HW(window(AirPassengers, end = c(1959, 12)), window(AirPassengers, start = 1960), 0.5)
Periodogram Data.frame
df_periods(x)
df_periods(x)
x |
a ts object. |
data.frame
Diego Jimenez <[email protected]>
df_periods(AirPassengers)
df_periods(AirPassengers)
Data.frame with normal test
dfnormal(data)
dfnormal(data)
data |
a data.frame object only with the numeric columns. |
data.frame
Diego Jimenez <[email protected]>
dfnormal(iris[, -5])
dfnormal(iris[, -5])
Best parameters arima model
e_acf(x)
e_acf(x)
x |
a ts object. |
echarts4r plot
Diego Jimenez <[email protected]>
e_acf(AirPassengers)
e_acf(AirPassengers)
Decompose plot
e_decompose(serie, f = NULL, noms = NULL)
e_decompose(serie, f = NULL, noms = NULL)
serie |
a ts object. |
f |
vector of dates for the time series. |
noms |
vector of names for y axis. |
echarts4r plot
Diego Jimenez <[email protected]>
e_decompose(AirPassengers)
e_decompose(AirPassengers)
Normal plot
e_histnormal( data, colorbar = "steelblue", colorline = "gray", nombres = c("Histograma", "Curva Normal") )
e_histnormal( data, colorbar = "steelblue", colorline = "gray", nombres = c("Histograma", "Curva Normal") )
data |
a numeric column of a data.frame. |
colorbar |
a color for the bars. |
colorline |
a color for the line. |
nombres |
a character vector of length 2 specifying the titles to use on legend. |
echarts4r plot
Diego Jimenez <[email protected]>
e_histnormal(iris$Sepal.Length)
e_histnormal(iris$Sepal.Length)
Best parameters arima model
e_pacf(x)
e_pacf(x)
x |
a ts object. |
echarts4r plot
Diego Jimenez <[email protected]>
e_pacf(AirPassengers)
e_pacf(AirPassengers)
Periodogram Plot
e_periods(x, p = NULL, noms = NULL)
e_periods(x, p = NULL, noms = NULL)
x |
a ts object. |
p |
which important period to plot. |
noms |
vector of lenght 3 to indicate the text to use. |
echarts4r plot
Diego Jimenez <[email protected]>
e_periods(AirPassengers)
e_periods(AirPassengers)
Qplot + Qline
e_qq(data, colorpoint = "steelblue", colorline = "gray")
e_qq(data, colorpoint = "steelblue", colorline = "gray")
data |
a numeric column of a data.frame. |
colorpoint |
a color for the points. |
colorline |
a color for the line. |
echarts4r plot
Diego Jimenez <[email protected]>
e_qq(iris$Sepal.Length)
e_qq(iris$Sepal.Length)
Tendencia y Estacionalidad
e_tc(x, d = NULL, noms = c("Time Series", "Trend", "Cyclicality"))
e_tc(x, d = NULL, noms = c("Time Series", "Trend", "Cyclicality"))
x |
a ts object. |
d |
a vector of dates to use on axis x (Optional). |
noms |
a vector of 3 to indicate the names to use on legend. |
data.frame
Diego Jimenez <[email protected]>
e_tc(AirPassengers)
e_tc(AirPassengers)
A web application for displaying, analysing and forecasting univariate time series. Includes basic methods such as mean, naïve, seasonal naïve and drift, as well as more complex methods such as Holt-Winters Box,G and Jenkins, G (1976) <doi:10.1111/jtsa.12194> and ARIMA Brockwell, P.J. and R.A.Davis (1991) <doi:10.1007/978-1-4419-0320-4>.
Package: | forecasteR |
Type: | Package |
Version: | 3.0.2 |
Date: | 2024-11-25 |
License: | GPL (>=2) |
Maintainer: Oldemar Rodriguez Rojas <[email protected]>
Oldemar Rodriguez Rojas <[email protected]>
Diego Jiménez Alvarado
Useful links:
Report bugs at https://github.com/PROMiDAT/forecasteR/issues
Get ts start of a time series
get_start(ini, tipo_f, patron)
get_start(ini, tipo_f, patron)
ini |
a Date object. |
tipo_f |
type of the time series ('year', 'month', ..., 'seconds'). |
patron |
frequency of time series. |
numeric vector of lenght 2
Diego Jimenez <[email protected]>
get_start(as.Date("2021-06-30"), 'days', 365)
get_start(as.Date("2021-06-30"), 'days', 365)
Error plot for all predictions
grafico.errores(errores)
grafico.errores(errores)
errores |
a data.frame with errors of a time series. |
data.frame
Diego Jimenez <[email protected]>
model <- arima(window(AirPassengers, end = c(1959, 12))) pred <- predict(model, 12) e <- tabla.errores(list(pred$pred), window(AirPassengers, start = 1960)) grafico.errores(e)
model <- arima(window(AirPassengers, end = c(1959, 12))) pred <- predict(model, 12) e <- tabla.errores(list(pred$pred), window(AirPassengers, start = 1960)) grafico.errores(e)
Mean Square Error
MSE(Pred, Real)
MSE(Pred, Real)
Pred |
a ts object (prediction). |
Real |
a ts object (real). |
numeric
Diego Jimenez <[email protected]>
model <- arima(window(AirPassengers, end = c(1959, 12))) pred <- predict(model, 12) MSE(pred$pred, window(AirPassengers, start = 1960))
model <- arima(window(AirPassengers, end = c(1959, 12))) pred <- predict(model, 12) MSE(pred$pred, window(AirPassengers, start = 1960))
Relative Error
RE(Pred, Real)
RE(Pred, Real)
Pred |
a ts object (prediction). |
Real |
a ts object (real). |
numeric
Diego Jimenez <[email protected]>
model <- arima(window(AirPassengers, end = c(1959, 12))) pred <- predict(model, 12) RE(pred$pred, window(AirPassengers, start = 1960))
model <- arima(window(AirPassengers, end = c(1959, 12))) pred <- predict(model, 12) RE(pred$pred, window(AirPassengers, start = 1960))
Root Mean Square Error
RMSE(Pred, Real)
RMSE(Pred, Real)
Pred |
a ts object (prediction). |
Real |
a ts object (real). |
numeric
Diego Jimenez <[email protected]>
model <- arima(window(AirPassengers, end = c(1959, 12))) pred <- predict(model, 12) RMSE(pred$pred, window(AirPassengers, start = 1960))
model <- arima(window(AirPassengers, end = c(1959, 12))) pred <- predict(model, 12) RMSE(pred$pred, window(AirPassengers, start = 1960))
RSS
RSS(Pred, Real)
RSS(Pred, Real)
Pred |
a ts object (prediction). |
Real |
a ts object (real). |
numeric
Diego Jimenez <[email protected]>
model <- arima(window(AirPassengers, end = c(1959, 12))) pred <- predict(model, 12) RSS(pred$pred, window(AirPassengers, start = 1960))
model <- arima(window(AirPassengers, end = c(1959, 12))) pred <- predict(model, 12) RSS(pred$pred, window(AirPassengers, start = 1960))
Run the Shiny Application
run_app(...)
run_app(...)
... |
A series of options to be used inside the app. |
Apply rolling to a numeric vector.
smoothing(v, n)
smoothing(v, n)
v |
a numeric vector. |
n |
integer value specifying the window width. |
numeric vector
Diego Jimenez <[email protected]>
smoothing(AirPassengers, 5)
smoothing(AirPassengers, 5)
Error table for all predictions
tabla.errores(Preds, Real, nombres = NULL)
tabla.errores(Preds, Real, nombres = NULL)
Preds |
a list of ts objects (prediction). |
Real |
a ts object (real). |
nombres |
names for the data.frame (optional). |
data.frame
Diego Jimenez <[email protected]>
model <- arima(window(AirPassengers, end = c(1959, 12))) pred <- predict(model, 12) tabla.errores(list(pred$pred), window(AirPassengers, start = 1960))
model <- arima(window(AirPassengers, end = c(1959, 12))) pred <- predict(model, 12) tabla.errores(list(pred$pred), window(AirPassengers, start = 1960))
Convert character to dates
text_toDate(f)
text_toDate(f)
f |
a vector of character. |
list
Diego Jimenez <[email protected]>
text_toDate(c("2023 january 27", "2023 january 28"))
text_toDate(c("2023 january 27", "2023 january 28"))
Filter category variables of a data.frame
var.categoricas(data)
var.categoricas(data)
data |
a data.frame object. |
data.frame
Diego Jimenez <[email protected]>
var.categoricas(iris)
var.categoricas(iris)
Filter numeric variables of a data.frame
var.numericas(data)
var.numericas(data)
data |
a data.frame object. |
data.frame
Diego Jimenez <[email protected]>
var.numericas(iris)
var.numericas(iris)