getTpPrediction: getTpPrediction
In teddiekgb/SportsData.TpPredict:

Description Usage Arguments Examples

View source: R/getTpPrediction.R

Generates the transition probabilties of a discrete time Markov chain using a set of pre-trained multinomial logistic regression models

1	getTpPrediction(AWAY_EFG, AWAY_TOVr, AWAY_OREBr, AWAY_DREBr, AWAY_FTF, AWAY_oEFG, AWAY_oTOVr, AWAY_oFTF, HOME_EFG, HOME_TOVr, HOME_OREBr, HOME_DREBr, HOME_FTF, HOME_oEFG, HOME_oTOVr, HOME_oFTF)

`AWAY_EFG`	A conitinuous time Markov-chain generator matrix.
`AWAY_TOVr`	Number of times to simulate the game.
`AWAY_OREBr`	Amount of game clock deciseconds to run each game simulation for.
`AWAY_DREBr`	A conitinuous time Markov-chain generator matrix.
`AWAY_FTF`	Number of times to simulate the game.
`AWAY_oEFG`	Amount of game clock deciseconds to run each game simulation for.
`AWAY_oTOVr`	A conitinuous time Markov-chain generator matrix.
`AWAY_oFTF`	Number of times to simulate the game.
`HOME_EFG`	A conitinuous time Markov-chain generator matrix.
`HOME_TOVr`	Number of times to simulate the game.
`HOME_OREBr`	Amount of game clock deciseconds to run each game simulation for.
`HOME_DREBr`	A conitinuous time Markov-chain generator matrix.
`HOME_FTF`	Number of times to simulate the game.
`HOME_oEFG`	Amount of game clock deciseconds to run each game simulation for.
`HOME_oTOVr`	A conitinuous time Markov-chain generator matrix.
`HOME_oFTF`	Number of times to simulate the game.

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (x)
{
  }