In msperlin/adfeR: Data, exercises and Functions for Book "Analise de Dados Financeiros e Economicos com o R"

set.seed(5)

# number of obs
n_row <- 100

# set x as Normal (0, 1)
x <- rnorm(n_row)

# set coefficients
my_alpha <- 1.5
my_beta <- 0.5

# build y
y <- my_alpha + my_beta*x + rnorm(n_row)

library(tidyverse)

my_lm <- lm(formula = y ~ x, data = tibble(x, y))

summary(my_lm)

library(car)

# set test matrix
test_matrix <- matrix(c(my_alpha,  # alpha test value
                        my_beta))  # beta test value

# hypothesis matrix 
hyp_mat <- matrix(c(1.5, 0,
                    0  , 0.5),
                  nrow = 2)

# do test
my_waldtest <- linearHypothesis(my_lm, 
                                hypothesis.matrix = hyp_mat, 
                                rhs = test_matrix)

# print result
my_sol <- my_waldtest$F[2]

# none
my_answers <- make_random_answers(my_sol)

Question

Utilizando pacote car, teste a hipótese conjunta de que o valor de alpha é igual a 1.5 e beta igual a 0.5. Qual o valor do teste F resultante?

exams::answerlist(my_answers, markup = "markdown")

Solution

Meta-information

extype: schoice exsolution: r mchoice2string(c(TRUE, FALSE, FALSE, FALSE, FALSE), single = TRUE) exname: "function 01" exshuffle: TRUE

msperlin/adfeR documentation built on March 26, 2021, 3:05 a.m.