optim_model_space {bdsm} | R Documentation |
Calculation of the model_space object
Description
This function calculates model space, values of the maximized likelihood function, BICs, and standard deviations of the parameters that will be used in Bayesian model averaging.
Usage
optim_model_space(
df,
timestamp_col,
entity_col,
dep_var_col,
init_value,
exact_value = FALSE,
cl = NULL,
control = list(trace = 2, maxit = 10000, fnscale = -1, REPORT = 100, scale = 0.05)
)
Arguments
df |
Data frame with data for the analysis. |
timestamp_col |
The name of the column with time stamps |
entity_col |
Column with entities (e.g. countries) |
dep_var_col |
Column with the dependent variable |
init_value |
The value with which the model space will be initialized. This will be the starting point for the numerical optimization. |
exact_value |
Whether the exact value of the likelihood should be
computed ( |
cl |
An optional cluster object. If supplied, the function will use this
cluster for parallel processing. If |
control |
a list of control parameters for the optimization which are
passed to optim. Default is
|
Value
List with two objects:
params - table with parameters of all estimated models
stats - table with the value of maximized likelihood function, BIC, and standard errors for all estimated models
Examples
## Not run:
library(magrittr)
data_prepared <- bdsm::economic_growth[, 1:5] %>%
bdsm::feature_standardization(
excluded_cols = c(country, year, gdp)
) %>%
bdsm::feature_standardization(
group_by_col = year,
excluded_cols = country,
scale = FALSE
)
optim_model_space(
df = data_prepared,
dep_var_col = gdp,
timestamp_col = year,
entity_col = country,
init_value = 0.5
)
## End(Not run)