Αποτελέσματα Αναζήτησης
model.matrix creates a design (or model) matrix, e.g., by expanding factors to a set of dummy variables (depending on the contrasts) and expanding interactions similarly.
R can be regarded as an implementation of the S language which was developed at Bell Labora- tories by Rick Becker, John Chambers and Allan Wilks, and also forms the basis of the S-Plus systems.
function. Creating tables of dummy variables for use in statistical modelling is extremely easy with the model.matrix function. You will see what the function does with a simple example. Suppose that our dataframe contains a factor called parasite indicating the identity of a gut parasite.
In R, ‘model.matrix’ is a useful tool for seeing the design matrices that are in play when you build regression models. Build a simple data frame. First, build a simple data frame with time as a factor and Time as a continuous, numeric variable. The two variables look alike when you print the data frame.
ample linear models, classical tests, a huge collection of high-level plotting functions or tools for survival analysis; many of these will be described and used in later chapters.
R provides an interlocking suite of facilities that make fitting statistical models very simple. As we mention in the introduction, the basic output is minimal, and one needs to ask for the details by calling extractor functions. 11.1 Defining statistical models; formulae.
Learning objectives: Install and load R packages Find package and function documentation Load external data into R Create and query vectors, matrices, and data frames Compute descriptive statistics and regression models Construct basic graphical displays.
