From 03eeca4e13b7cd9fcdb7a7745d32f4d8c63ed04a Mon Sep 17 00:00:00 2001 From: Walmes Zeviani <walmes@ufpr.br> Date: Tue, 3 May 2016 15:48:06 -0300 Subject: [PATCH] =?UTF-8?q?Melhora=20a=20exibi=C3=A7=C3=A3o=20do=20espa?= =?UTF-8?q?=C3=A7o=20param=C3=A9trico.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- vignettes/v04_poisson_generelizada.Rmd | 25 +++++-------------------- 1 file changed, 5 insertions(+), 20 deletions(-) diff --git a/vignettes/v04_poisson_generelizada.Rmd b/vignettes/v04_poisson_generelizada.Rmd index bbe4b67..fdada46 100644 --- a/vignettes/v04_poisson_generelizada.Rmd +++ b/vignettes/v04_poisson_generelizada.Rmd @@ -142,13 +142,13 @@ rp.do(panel = panel, action = react) library(latticeExtra) -y <- 0:50 +y <- 0:200 fun <- Vectorize(vectorize.args = c("theta", "gamma"), FUN = function(theta, gamma) { sum(dpg0(y = y, theta = theta, gamma = gamma)) }) -grid <- list(theta = seq(0.1, 10, by = 0.1), +grid <- list(theta = seq(0.5, 50, by = 0.5), gamma = seq(-0.98, 0.98, by = 0.02)) grid$sum <- with(grid, outer(theta, gamma, fun)) grid <- with(grid, @@ -156,15 +156,13 @@ grid <- with(grid, data.frame(sum = c(sum)))) # levelplot(sum ~ theta + gamma, data = grid, -# col.regions = heat.colors) + +# col.regions = gray.colors) + # layer(panel.abline(h = 0)) levelplot(sum ~ theta + gamma, data = subset(grid, round(sum, 3) == 1), - col.regions = heat.colors) + - layer(panel.abline(h = 0)) - -subset(grid, round(sum, 3) != 1 & theta > 6 & gamma < 0) + col.regions = gray.colors) + + layer(panel.abline(a = 0, b = -1/200)) ``` ## Modelo de Regressão com a Distribuição Poisson Generalizada ## @@ -365,18 +363,6 @@ m3 <- mle2(llpg, start = start, data = L, vecpar = TRUE) # Teste para nulinidade do parâmetro de dispersão (H_0: alpha == 0). anova(m3, m2) -# est_stderr <- function(tb) { -# sprintf("%s (%0.4f)", -# formatC(tb[, 1], flag = " ", digits = 4, format = "f"), -# tb[, 2]) -# } -# -# L <- list("PoissonGLM" = rbind(NA, summary(m0)$coef), -# "PoissonML*" = rbind(NA, summary(m2)@coef), -# "PGeneraliz" = summary(m3)@coef) -# -# as.data.frame(sapply(L, est_stderr)) - cbind("PoissonGLM" = c(NA, coef(m0)), "PoissonML" = coef(m2), "PGeneraliz" = coef(m3)) @@ -450,7 +436,6 @@ V <- V[-1, -1] U <- chol(V) aux <- sqrt(apply(X %*% t(U), MARGIN = 1, FUN = function(x) { sum(x^2) })) - pred$pgen$eta <- c(X %*% coef(m3)[-1]) pred$pgen <- cbind(pred$pgen, apply(outer(aux, qn, FUN = "*"), MARGIN = 2, -- GitLab