| df_stationarity {DescribeDF} | R Documentation |
Descriptive Statistics of A Data Frame
Description
Gives a list of three data frames: 'ADF', 'PP', 'KPSS'. This will also indicate whether the data is stationary or not according to the null hypothesis of the corresponding tests. The data frame must contain serial number or date or anything in the 1st column.This function will exclude the 1st column of the data frame and will perform tests on other columns. "p_value <= 0.01: ***; p_value <= 0.05: **; p_value <= 0.1: *".
Usage
df_stationarity(df)
Arguments
df |
Data Frame with first column as serial number or date |
Value
test_results - List of three data frames: 'ADF', 'PP', 'KPSS'
References
Garai, S., & Paul, R. K. (2023). Development of MCS based-ensemble models using CEEMDAN decomposition and machine intelligence. Intelligent Systems with Applications, 18, 200202.
Garai, S., Paul, R. K., Rakshit, D., Yeasin, M., Paul, A. K., Roy, H. S., Barman, S. & Manjunatha, B. (2023). An MRA Based MLR Model for Forecasting Indian Annual Rainfall Using Large Scale Climate Indices. International Journal of Environment and Climate Change, 13(5), 137-150.
Examples
# create a vector of dates
dates <- seq(as.Date("2021-01-01"), as.Date("2021-01-05"), by = "day")
# create vectors of random numeric data for columns A through E
A <- runif(5, 0, 1)
B <- runif(5, 0, 1)
C <- runif(5, 0, 1)
D <- runif(5, 0, 1)
E <- runif(5, 0, 1)
# combine the vectors into a data frame
df <- data.frame(Date = dates, A = A, B = B, C = C, D = D, E = E)
# print the data frame
print(df)
# stationarity results
df_stationarity(df)