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What is scale parameter in GLM?
The scale parameter is an estimated model parameter related to the variance of the response. The scale weights are “known” values that can vary from observation to observation. Cases with scale weight values that are less than or equal to 0 or are missing are not used in the analysis.
What is scale weight variable?
The scale weights are “known” values that can vary from observation to observation. If the scale weight variable is specified, the scale parameter, which is related to the variance of the response, is divided by it for each observation.
Is the scale parameter the same as the dispersion parameter?
Yes, in generalized linear model (GLM) theory, you can assume that the “dispersion” parameter and the “scale” parameter are the same thing. Roughly speaking, “scale” is the older GLIM terminology and “dispersion” is the newer R terminology.
Which is the dispersion parameter in the GLM?
Y i ∼ P o i s s o n ( λ). However, you have only one parameter here! The single parameter λ determines both mean and variance by E [ Y i] = λ and V a r [ Y i] = λ. This also happens when you use Bernoulli or binomial distribution.
What is the dispersion parameter in a generalized linear model?
The dispersion parameter, The resulting model is known as logistic regression (or multinomial logistic regression in the case that K-way rather than binary values are being predicted). For the Bernoulli and binomial distributions, the parameter is a single probability, indicating the likelihood of occurrence of a single event.
Which is the correct terminology scale or dispersion?
Roughly speaking, “scale” is the older GLIM terminology and “dispersion” is the newer R terminology. However, the term “scale” has been used inconsistently in GLM terminology and so is best avoided (IMO). where a () is a known function of the (possibly unknown) parameter ϕ .