B_T_Weighted_fp: Bradley-Terry Weighted Likelihood Function with home...

In heilokchow/MWLE-Lasso: Bradley-Terry Model with Exponential Decayed Likelihood function and Lasso Penalty

Description

Bradley-Terry Weighted Likelihood Function with home parameter for Likelihood Ratio Test of abilities time constancy

Usage

B_T_Weighted_fp(df, ability, uf, u, i0, date)

Arguments

df	Dataframe with 5 columns. First column is the index of the home teams (use numbers to denote teams). Second column is the index of the away teams. Third column is the number of wins of home teams (usually to be 0/1). Fourth column is the number of wins of away teams (usually to be 0/1). Fifth column is the scalar of time when the match is played until now (Time lag).
ability	A column vector of teams ability, the last row is the home parameter whose rowname must be "at.home". The row number is consistent with the team's index shown in dataframe. Column name must be "xn".
uf	Team index whose time constancy will be tested.
u	The exponential decay rate.
i0	is a teams index whose ability will be fixed as 0 (usually the team loss most).
date	the date were selected team will have different abilities before and after (usually chosen to be the mid time when abilities are expected to change).

Value

The estimated abilities.

heilokchow/MWLE-Lasso documentation built on May 23, 2019, 4:03 a.m.