Nothing
## ----setup, include=FALSE-----------------------------------------------------
library(knitr)
knitr::opts_chunk$set(
fig.align = "center",
fig.height = 5.5,
fig.width = 6,
warning = FALSE,
collapse = TRUE,
dev.args = list(pointsize = 10),
out.width = "90%",
par = TRUE
)
knit_hooks$set(par = function(before, options, envir)
{ if (before && options$fig.show != "none")
par(family = "sans", mar = c(4.1,4.1,1.1,1.1), mgp = c(3,1,0), tcl = -0.5)
})
## ---- message = FALSE, echo = FALSE-------------------------------------------
library(meteorits)
## -----------------------------------------------------------------------------
n <- 500 # Size of the sample
alphak <- matrix(c(0, 8), ncol = 1) # Parameters of the gating network
betak <- matrix(c(0, -2.5, 0, 2.5), ncol = 2) # Regression coefficients of the experts
sigmak <- c(1, 1) # Standard deviations of the experts
x <- seq.int(from = -1, to = 1, length.out = n) # Inputs (predictors)
# Generate sample of size n
sample <- sampleUnivNMoE(alphak = alphak, betak = betak, sigmak = sigmak, x = x)
y <- sample$y
## -----------------------------------------------------------------------------
K <- 2 # Number of regressors/experts
p <- 1 # Order of the polynomial regression (regressors/experts)
q <- 1 # Order of the logistic regression (gating network)
## -----------------------------------------------------------------------------
n_tries <- 1
max_iter <- 1500
threshold <- 1e-5
verbose <- TRUE
verbose_IRLS <- FALSE
## -----------------------------------------------------------------------------
nmoe <- emNMoE(X = x, Y = y, K, p, q, n_tries, max_iter,
threshold, verbose, verbose_IRLS)
## -----------------------------------------------------------------------------
nmoe$summary()
## -----------------------------------------------------------------------------
nmoe$plot(what = "meancurve")
## -----------------------------------------------------------------------------
nmoe$plot(what = "confregions")
## -----------------------------------------------------------------------------
nmoe$plot(what = "clusters")
## -----------------------------------------------------------------------------
nmoe$plot(what = "loglikelihood")
## -----------------------------------------------------------------------------
data("tempanomalies")
x <- tempanomalies$Year
y <- tempanomalies$AnnualAnomaly
## -----------------------------------------------------------------------------
K <- 2 # Number of regressors/experts
p <- 1 # Order of the polynomial regression (regressors/experts)
q <- 1 # Order of the logistic regression (gating network)
## -----------------------------------------------------------------------------
n_tries <- 1
max_iter <- 1500
threshold <- 1e-5
verbose <- TRUE
verbose_IRLS <- FALSE
## -----------------------------------------------------------------------------
nmoe <- emNMoE(X = x, Y = y, K, p, q, n_tries, max_iter,
threshold, verbose, verbose_IRLS)
## -----------------------------------------------------------------------------
nmoe$summary()
## -----------------------------------------------------------------------------
nmoe$plot(what = "meancurve")
## -----------------------------------------------------------------------------
nmoe$plot(what = "confregions")
## -----------------------------------------------------------------------------
nmoe$plot(what = "clusters")
## -----------------------------------------------------------------------------
nmoe$plot(what = "loglikelihood")
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