fitH1Model {TPP2D} | R Documentation

## Fit H1 model and evaluate fit statistics

### Description

Fit H1 model and evaluate fit statistics

### Usage

    fitH1Model(
      df,
      maxit = 500,
      optim_fun = .min_RSS_h1_slope_pEC50,
      optim_fun_2 = NULL,
      gr_fun = NULL,
      gr_fun_2 = NULL,
      ec50_lower_limit = NULL,
      ec50_upper_limit = NULL,
      slopEC50 = TRUE
    )

### Arguments

`df` | tidy data_frame retrieved after import of a 2D-TPP dataset, potential filtering and addition of a column "nObs" containing the number of observations per protein
`maxit` | maximal number of iterations the optimization should be given, default is set to 500
`optim_fun` | optimization function that should be used for fitting the H0 model
`optim_fun_2` | optional secound optimization function for fitting the H1 model that should be used based on the fitted parameters of the optimizationfor based on optim_fun
`gr_fun` | optional gradient function for optim_fun, default is NULL
`gr_fun_2` | optional gradient function for optim_fun_2, default is NULL
`ec50_lower_limit` | lower limit of ec50 parameter
`ec50_upper_limit` | lower limit of ec50 parameter
`slopEC50` | logical flag indicating whether the h1 model is fitted with a linear model describing the shift od the pEC50 over temperatures

### Value

data frame with H1 model characteristics for each protein

### Examples

    data("simulated_cell_extract_df")
    temp_df <- simulated_cell_extract_df %>%
      filter(clustername %in% paste0("protein", 1:5)) %>%
      group_by(representative) %>%
      mutate(nObs = n()) %>%
      ungroup

    fitH1Model(temp_df)

[Package TPP2D version 1.8.0 Index]