add contributor

DESCRIPTION

@@ -8,10 +8,12 @@ Authors@R: c(
         email = "[email protected]",
         role = c("aut", "cre", "cph"), 
         comment = c(ORCID = "0000-0001-5375-9967")),
+    person("Hugo",
+        "Najberg",
+        role = "ctb"),
     person("Viliam",
         "Simko",
-        role = "ctb",
-        email = "[email protected]"),
+        role = "ctb"),
     person("Sasha", 
         "Epskamp", 
         role = "rev",

R/simulate.R

@@ -2,37 +2,56 @@
 #'
 #' Simulates data for single or multiple regression.
 #'
-#' @param sample Desired sample size.
 #' @param coefs Desired theorethical coefs. Can be a single value or a list.
+#' @param sample Desired sample size.
 #' @param error The error (standard deviation of gaussian noise).
 #'
 #' @examples
 #' library(psycho)
 #'
-#' data <- simulate_data_regression(sample=50, coefs=c(0, 0.5), error=0.1)
-#' lm(y ~ ., data=data)
+#' data <- simulate_data_regression(coefs=c(0, 0.8), sample=50, error=0)
+#' fit <- lm(y ~ ., data=data)
+#' coef(fit)
+#' analyze(fit)
 #'
 #' @details See https://stats.stackexchange.com/questions/59062/multiple-linear-regression-simulation
 #'
 #' @author TPArrow
 #'
 #' @export
-simulate_data_regression <- function(sample=10, coefs=0, error=0){
+simulate_data_regression <- function(coefs=0.5, sample=100, error=0){
+
+  # Prevent error
+  coefs[coefs == 0] <- 0.01
+
+  y <- rnorm(sample, 0, 1)
+
+  n_var <- length(coefs)
+  X <- scale(matrix(rnorm(sample*(n_var), 0, 1), ncol=n_var))
+  X <- cbind(y, X)
 
-  n_var = length(coefs)
-  X = matrix(0, ncol=n_var, nrow=sample)
+  # find the current correlation matrix
+  cor_0 <- var(X)
 
-  beta = as.matrix(coefs)
+  # cholesky decomposition to get independence
+  chol_0 <- solve(chol(cor_0))
 
-  for (i in 1:n_var){
-    X[,i] = rnorm(sample, 0, 1)
-  }
+  X <-  X %*% chol_0
 
-  y = X %*% beta + rnorm(sample, 0, error)
-  data = data.frame(X=X)
+  # create new correlation structure (zeros can be replaced with other r vals)
+  coefs_structure <- diag(x = 1, nrow=n_var+1, ncol=n_var+1, names = TRUE)
+  coefs_structure[-1, 1] <- coefs
+  coefs_structure[1, -1] <- coefs
+
+  X <- X %*% chol(coefs_structure) * sd(y) + mean(y)
+  X <- X[,-1]
+
+  # Add noise
+  y <- y + rnorm(sample, 0, error)
+
+  data <- data.frame(X)
   names(data) <- paste0("V", 1:n_var)
-  data$y <- y
+  data$y <- as.vector(y)
 
   return(data)
 }
-

docs/index.html

@@ -14,7 +14,7 @@ <h1 class="page-heading">About</h1>
 
   <h1 class="page-heading">People</h1>
 
-  <b>Current <a href="https://github.com/neuropsychology/psycho.R/graphs/contributors">contributors</a> are <a href="https://dominiquemakowski.github.io/">D. Makowski</a>, <a href="https://github.com/vsimko">V. Simko</a>, and <a href="https://github.com/neuropsychology/psycho.R/blob/master/.github/CONTRIBUTING.md">YOU?</a></b>
+  <b>Current <a href="https://github.com/neuropsychology/psycho.R/graphs/contributors">contributors</a> are <a href="https://dominiquemakowski.github.io/">D. Makowski</a>, <a href="https://github.com/HugoNjb">H. Najberg</a>, <a href="https://github.com/vsimko">V. Simko</a>, and <a href="https://github.com/neuropsychology/psycho.R/blob/master/.github/CONTRIBUTING.md">YOU?</a></b>
 
   <h1 class="page-heading">Posts</h1>