View source: R/bootstrap_param_est.R

bootstrap_param_est | R Documentation |

Fits a Markov model then bootstraps the data and refits the model.

bootstrap_param_est( wide, b, days = paste0("D", 1:28), bin = rep(1, length(days) - 1), Em = get_emission(wide, days), tol = 1e-06, maxiter = 200, silent = FALSE )

`wide` |
Data in wide format (i.e., each day is a column). See details. |

`b` |
Number of bootstrap samples to take. |

`days` |
Names of the columns that contain the score for each day. |

`bin` |
The assigned bin for pooling together information across transitions. Must be a numeric vector of length=(length(days)-1). By default all transitions are pooled together. |

`Em` |
Emission probabilities. Default should be used unless user is advanced. |

`tol` |
Tolerance for relative reduction the log-likelihood to determine convergence of the Baum-Welch algorythm. |

`maxiter` |
Maximum iterations before stopping the EM algorithm. |

`silent` |
Allows silencing some messages. |

States for each patient/day in 'wide' may be the following:

Not missing:An integer from 1 to 8.

Missing:NA

Partially Missing: range which may be code as a characters string such as '[1,7]' or '[1,2]'. Such a character string indicates that while the actual value is unknown, it is known that the value falls within the specified range.

Generally the user will not need to call this function directly because it is called by the 'impute' function.

A list object with the following components:

- fit
Contains results of the primary model fit

- boot
Contains relults from the bootstrap model fit.

- bin
The input.

- s
Ignor. May be used in future.

- days
From input.

- Em
From input.

`impute`

test <- sim_data(100) bs <- bootstrap_param_est(wide=test,b=2)

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