ff {MB}

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)

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))

Value

the output from ff()

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)