# Calculating IC weights based on IC values (AIC, ORIC, GORIC(A), BIC, SIC, ...) This function transforms IC values into IC weights: IC values denote the ordering of hypotheses/models, while IC weights quantify the relative strength of hypotheses/models. ```r calculate_IC_weights(IC, hypo_names = NULL, use_scientific = TRUE) calc_ICweights(IC, hypo_names = NULL, use_scientific = TRUE) ## S3 method for class 'goric_ICw' print(x, digits = max(3, getOption("digits") - 4), ...) ``` ## Arguments - `IC`: A vector or one-column matrix with information criteria (AIC, ORIC, GORIC(A), BIC, SIC, ) values of length 'NrHypos', where 'NrHypos' stands for the number of hypotheses/ models. - `x`: an object of class `con_goric`. - `hypo_names`: Optional. Vector containing 'NrHypos' characters which will be used for labeling the hypothesis. Default: H1, H2, - `use_scientific`: If TRUE (default), the IC weights and ratio of IC weights will be formatted using scientific notation. If FALSE, standard numeric formatting is used. - `digits`: the number of significant digits to use when printing. - ``: no additional arguments for now. ## Returns IC weights, which quantify the relative strength of hypotheses/models. ## Examples ```r IC <- c(1,2,3) calculate_IC_weights(IC) ## PT weights # This examples shows how to calculate PT weights. # Notably, one is interested in PT weights when the log-likelihood for two or more # hypotheses are (approximately) equal. # Then, the comparison between those hypotheses is solely based on the PT values. # The IC weights will then equal the PT weights. # In that case, there is support for the overlap (boundary) of these hypotheses. # Thus, when the IC weights equal the PT weights for a (sub)set of hypotheses, # then there is support for the overlap (boundary) of these hypotheses. y <- rnorm(30) group <- factor(rep(c("A","B","C"), each = 10)) fit.lm <- lm(y ~ -1 + group) est <- coef(fit.lm) VCOV_est <- vcov(fit.lm) H1 <- "groupA < groupB < groupC" results <- goric(est, VCOV = VCOV_est, hypotheses = list(H1), comparison = "complement", type = "gorica") calculate_IC_weights(results$result[,3]) ```

calculate_IC_weights function