pd_lm.fit {proDA} | R Documentation

## The work horse for fitting the probabilistic dropout model

### Description

If there is no location and variance moderation and no missing values, the model is fitted with 'lm'.

### Usage

    pd_lm.fit(
      y,
      X,
      dropout_curve_position,
      dropout_curve_scale,
      location_prior_mean = NULL,
      location_prior_scale = NULL,
      variance_prior_scale = NULL,
      variance_prior_df = NULL,
      location_prior_df = 3,
      method = c("analytic_hessian", "analytic_grad", "numeric"),
      verbose = FALSE
    )

### Value

a list with the following entries

coefficients

  a named vector with the fitted values

n_approx

  the estimated "size" of the data set (n_hat - variance_prior_df)

df

  the estimated degrees of freedom (n_hat - p)

s2

  the estimated unbiased variance

n_obs

  the number of response values that were not 'NA'

[Package proDA version 1.6.0 Index]