1d:T7b4,# Compares the BIC of several outputs This function is used to compare the BIC of several outputs obtained with the same data but with different set of parameters. Each object must have associated `logLik()` method with df and nobs attributes. BIC for object x will be calculated as `2*factor.value*sum(logLik(x))+sum(attributes(logLik(x))$df)*log(attributes(logLik(x))$nobs))`. When several data (i..n) are included, the global BIC is calculated as: `2*factor.value*sum(logLik(x)) for i..n+sum(attributes(logLik(x))$df)for i..n*log(attributes(logLik(x))$nobs for i..n))` ```r compare_BIC( ..., factor.value = -1, silent = FALSE, FUN = function(x) specify_decimal(x, decimals = 2) ) ``` ## Arguments - `...`: Successive results to be compared as lists. - `factor.value`: The $value of the list object is multiplied by factor.value to calculate BIC. - `silent`: If TRUE, nothing is displayed. - `FUN`: Function used to show values ## Returns A list with DeltaBIC and Akaike weight for the models. ## Details compare_BIC compares the BIC of several outputs obtained with the same data. ## Examples ```r ## Not run: library("HelpersMG") # Here two different models are fitted x <- 1:30 y <- rnorm(30, 10, 2)+log(x) plot(x, y) d <- data.frame(x=x, y=y) m1 <- lm(y ~ x, data=d) m2 <- lm(y ~ log(x), data=d) compare_BIC(linear=m1, log=m2, factor.value=-1) # Here test if two datasets can be modeled with a single model x2 <- 1:30 y2 <- rnorm(30, 15, 2)+log(x2) plot(x, y, ylim=c(5, 25)) plot_add(x2, y2, col="red") d2 <- data.frame(x=x2, y=y2) m1_2 <- lm(y ~ x, data=d2) x_grouped <- c(x, x2) y_grouped <- c(y, y2) d_grouped <- data.frame(x=x_grouped, y=y_grouped) m1_grouped <- lm(y ~ x, data=d_grouped) compare_BIC(separate=list(m1, m1_2), grouped=m1_grouped, factor.value=-1) ## End(Not run) ``` ## See Also Other AIC: `ExtractAIC.glm()`, `FormatCompareAIC()`, `compare_AIC()`, `compare_AICc()` ## Author(s) Marc Girondot marc.girondot@gmail.com

compare_BIC function