use_generalised_linear_model: ############################################################################ Get the parameter values using logistic regression

Description

############################################################################ Get the parameter values using logistic regression

Usage

use_generalised_linear_model(
  param_to_be_estimated,
  dataset,
  indep_var,
  family,
  covariates,
  interaction,
  naaction,
  link = NA
)

Value

the results of the regression analysis

Arguments

param_to_be_estimated: parameter of interest
dataset: data set to be provided
indep_var: the independent variable (column name in data file)
family: distribution name eg. for logistic regression -binomial
covariates: list of covariates-calculations to be done before passing
interaction: boolean value to indicate interaction in the case of linear regression
naaction: action to be taken with the missing values
link: link function if not the default for each family

Details

This function returns the results and plots after doing linear regression Requires param to be estimated, dataset, independent variables and information on covariates, and interaction variables if there are Uses form_expression_glm to create the expression as per R standard for e.g glm(y ~ x ). Returns the fit result,s summary results as returned by summary(), confidence interval for fit coefficients (ci_coeff), variance covariance matrix, cholesky decomposition matrix, results from correlation test, plot of diagnostic tests and model fit assumptions, plot of model prediction diagnostic include AIC, R2, and BIC. The results of the prediction ie predicted values for fixed other variables will be returned in prediction matrix

Examples

Run this code

# \donttest{
gm_result <- use_generalised_linear_model(
  param_to_be_estimated = "Direction",
  dataset = ISLR::Smarket, indep_var = "Lag1", family = "binomial",
  covariates = c("Lag2", "Lag3"),
  interaction = FALSE, naaction = "na.omit", link = NA)
# }