Commit 229a5010 by Walmes Marques Zeviani

### Passa para baixo o estudo do espaço parametrico.

parent 03eeca4e
 ... ... @@ -134,37 +134,6 @@ rp.checkbox(panel = panel, rp.do(panel = panel, action = react)  ## O espaço paramétrico de $\theta$ e $\gamma$ ## {r} #----------------------------------------------------------------------- # Gráfico do espaço paramétrico de theta x gamma. library(latticeExtra) 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(0.5, 50, by = 0.5), gamma = seq(-0.98, 0.98, by = 0.02)) grid$sum <- with(grid, outer(theta, gamma, fun)) grid <- with(grid, cbind(expand.grid(theta = theta, gamma = gamma), data.frame(sum = c(sum)))) # levelplot(sum ~ theta + gamma, data = grid, # col.regions = gray.colors) + # layer(panel.abline(h = 0)) levelplot(sum ~ theta + gamma, data = subset(grid, round(sum, 3) == 1), col.regions = gray.colors) + layer(panel.abline(a = 0, b = -1/200))  ## Modelo de Regressão com a Distribuição Poisson Generalizada ## {r, eval=FALSE} ... ... @@ -173,10 +142,12 @@ dpg1 <- function(y, lambda, alpha) { k <- lfactorial(y) w <- 1 + alpha * y z <- 1 + alpha * lambda m <- alpha > pmax(-1/y, -1/lambda) # fy <- (lambda/z)^(y) * w^(y - 1) * exp(-lambda * (w/z))/exp(k) fy <- y * (log(lambda) - log(z)) + (y - 1) * log(w) - lambda * (w/z) - k return(exp(fy)) fy[!m] <- 0 return(m * exp(fy)) } react <- function(panel){ ... ... @@ -238,6 +209,58 @@ rp.checkbox(panel = panel, rp.do(panel = panel, action = react)  ## O espaço paramétrico ## {r} #----------------------------------------------------------------------- # Gráfico do espaço paramétrico de theta x gamma. # debug(dpg1) # dpg1(y = 0:10, lambda = 1, alpha = 0) # dpg1(y = 0:10, lambda = 1, alpha = -0.1) # undebug(dpg1) library(latticeExtra) y <- 0:200 fun <- Vectorize(vectorize.args = c("theta", "gamma"), FUN = function(theta, gamma) { sum(dpg0(y = y, theta = theta, gamma = gamma)) }) grid <- list(theta = seq(0.5, 50, by = 0.5), gamma = seq(-0.98, 0.98, by = 0.02)) grid$sum <- with(grid, outer(theta, gamma, fun)) grid <- with(grid, cbind(expand.grid(theta = theta, gamma = gamma), data.frame(sum = c(sum)))) levelplot(sum ~ theta + gamma, data = subset(grid, round(sum, 3) == 1), col.regions = gray.colors) + layer(panel.abline(a = 0, b = -1/200)) fun <- Vectorize(vectorize.args = c("lambda", "alpha"), FUN = function(lambda, alpha) { sum(dpg1(y = y, lambda = lambda, alpha = alpha)) }) dpg1(y = 0:10, lambda = 5, alpha = -0) dpois(0:10, lambda = 5) grid <- list(lambda = seq(0.2, 50, by = 0.2), alpha = seq(-0.98, 0.98, by = 0.02)) grid\$sum <- with(grid, outer(lambda, alpha, fun)) grid <- with(grid, cbind(expand.grid(lambda = lambda, alpha = alpha), data.frame(sum = c(sum)))) levelplot(sum ~ lambda + alpha, data = subset(grid, round(sum, 3) == 1), col.regions = gray.colors)  ## Verossimilhança e Estimação ## {r} ... ...
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