MB (version 0.1.1)

ff: The Use of Marginal Distributions in Conditional Forecasting

Description

A new way to predict time series using the marginal distribution table in the absence of the significance of traditional models.

Usage

ff(dt,m,w,n,q1)

Value

the output from ff()

Arguments

dt

data frame

m

the number of time series

w

the number of predicted values

n

number of values

q1

matrix independent time series values #In the case of m=2, enter the independent string values as follows(matrix(c())),In the case of m=3, enter the independent string values as follows(matrix(c(),w,m-1,byrow=T))

Examples

x=rnorm(17,10,1)
y=rnorm(17,10,1)
data=data.frame(x,y)
print("Enter independent time series values")
q1=list(q=matrix(c(scan(,,quiet=TRUE)),1,2-1))
10.5


ff(data,2,1,17,q1)