## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 7, fig.height = 7, fig.align = "center" ) ## ----setup-------------------------------------------------------------------- library(mixvlmc) library(geodist) ## used in the earth quake example library(ggplot2) ## used in the earth quake example ## ----echo=FALSE--------------------------------------------------------------- homc <- data.frame(m = 1:10) homc$parameters <- 3 * (4^homc$m) homc ## ----echo=FALSE--------------------------------------------------------------- bin_mark <- cbind( expand.grid("n-3" = 0:1, "n-2" = 0:1, "n-1" = 0:1), data.frame(Probablity = c(0.1, 0.1, 0.1, 0.1, 0.2, 0.4, 0.3, 0.3)) ) ## ----echo=FALSE--------------------------------------------------------------- bin_mark ## ----------------------------------------------------------------------------- set.seed(0) x <- sample(c(0L, 1L, 2L), 200, replace = TRUE) model <- vlmc(x) model ## ----------------------------------------------------------------------------- model_theo <- vlmc(x, cutoff = log(length(x))) model_theo ## ----------------------------------------------------------------------------- model_large <- vlmc(x, cutoff = 0.5 * log(length(x))) model_large model_cutoff <- cutoff(model_large, scale = "native") model_cutoff ## ----------------------------------------------------------------------------- model_medium <- prune(model_large, cutoff = model_cutoff[1]) model_medium ## ----------------------------------------------------------------------------- model_small <- prune(model_large, cutoff = model_cutoff[2]) model_small ## ----------------------------------------------------------------------------- model_tune <- tune_vlmc(x) model_opt <- as_vlmc(model_tune) model_opt ## ----------------------------------------------------------------------------- California_centre <- data.frame(longitude = -119.449444, latitude = 37.166111) distances <- geodist(globalearthquake[, c("longitude", "latitude")], California_centre, measure = "geodesic" ) California_earth_quakes <- globalearthquake[distances < 2e6, ] ## distances are in meters ## ----------------------------------------------------------------------------- California_weeks <- rep(0, max(globalearthquake$nbweeks)) California_weeks[California_earth_quakes$nbweeks] <- 1 ## ----------------------------------------------------------------------------- California_weeks_earth_quakes_model <- tune_vlmc(California_weeks, initial = "truncated") plot(California_weeks_earth_quakes_model) ## ----------------------------------------------------------------------------- draw(as_vlmc(California_weeks_earth_quakes_model)) ## ----------------------------------------------------------------------------- summary(California_weeks_earth_quakes_model) ## ----fig.height=4------------------------------------------------------------- ggplot(California_weeks_earth_quakes_model$results, aes(x = alpha, y = BIC)) + geom_line() + geom_point() ## ----------------------------------------------------------------------------- states(model_large) depth(model_large) context_number(model_large) ## ----------------------------------------------------------------------------- logLik(model_large) AIC(model_large) BIC(model_large) ## ----------------------------------------------------------------------------- draw(model_large) ## ----------------------------------------------------------------------------- contexts(model_large, cutoff = "native") ## ----------------------------------------------------------------------------- contexts(model_large, cutoff = "quantile", reverse = FALSE, frequency = "detailed") ## ----------------------------------------------------------------------------- ctxs <- contexts(model_large) ctxs ## ----------------------------------------------------------------------------- counts(ctxs[[2]]) cutoff(ctxs[[3]])