# Search results

1. ### How to calculate partial residuals by hand?

Code for GLM Poisson regression (R): library(datasets) mydata <- warpbreaks poisson_mod <- glm(breaks ~ wool + tension, mydata, family = poisson()) Gives: Call: glm(formula = breaks ~ wool + tension, family = poisson(link = "log"), data = mydata) Coefficients: (Intercept) woolB...
2. ### How family=Poisson works in glm function in R?

Let's assume I am working with this dataset on R: n <- 40 x1 <- rnorm(n, mean=3, sd=1) x2 <- rnorm(n, mean=4, sd=1.25) y <- 2*x1 + 3*x2 + rnorm(n, mean=2, sd=1) mydata <- data.frame(x1, x2, y) I cannot understand how Poisson regression works in R, I would assume that the following are...
3. ### Difference between simulating the dependent variable and simulating the error terms and adding them to the fitted values values assuming normality?

Ok thank you, this is very clear. It helped me a lot to understand the difference plotting X vs fitted.values, X vs option1 and X vs option2.
4. ### Difference between simulating the dependent variable and simulating the error terms and adding them to the fitted values values assuming normality?

The purpose is bootstrap dependent variable in generalized linear models
5. ### Difference between simulating the dependent variable and simulating the error terms and adding them to the fitted values values assuming normality?

What's the statistical difference between simulating the dependent variable and simulating the error terms and adding them to the fitted values values assuming normality (gaussian GLM)? Say I'm doing a simple multiple regression on the following data (R): n <- 40 x1 <- rnorm(n, mean=3, sd=1)...
6. ### Hypothesis test for the difference of two means, should I consider annualized or monthly returns?

I have 10 years monthly returns. I calculated annualized return multiplying the mean return over the period for 12. Then I calculated the excess returns as difference between the annualized mean return and the benchmark annualized mean return (no risk correction). Annualized standard deviations...