There are n = 14 observations yi. The assumed model is the Binomial distribution, each y; with a covariate observation xi. As part of this setting, there are parameters ₁, 2, ..., ₁4 that will be estimated. Match the following parameterizations with the model name. {π₁ = π₂ = ... = π14 = π} {♫₁ = g¯¹(Bo + B₁x1), π2 = g¯¹(Bo + B1X2), ..., π14 = g¯¹(ßo + B1×14)} {π₁, T₂, ...,14} Choose... Choose... Choose... ◆
There are n = 14 observations yi. The assumed model is the Binomial distribution, each y; with a covariate observation xi. As part of this setting, there are parameters ₁, 2, ..., ₁4 that will be estimated. Match the following parameterizations with the model name. {π₁ = π₂ = ... = π14 = π} {♫₁ = g¯¹(Bo + B₁x1), π2 = g¯¹(Bo + B1X2), ..., π14 = g¯¹(ßo + B1×14)} {π₁, T₂, ...,14} Choose... Choose... Choose... ◆
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Is it maximal model, logistic regression or null model?

Transcribed Image Text:There are n = 14 observations y¡ . The assumed model is the Binomial distribution, each y; with a covariate
that will be estimated. Match the
14
observation x;. As part of this setting, there are parameters 1, ₂,
following parameterizations with the model name.
{π₁ = π₂ =
π}
{л₁ = g¯¹ (Bo + B₁x₁), A₂ = g¯¹ (ß0 + B₁x₂),..., 14 = 8¯¹ (Bo + B₁X14)}
₂π14}
{π1, T2,
= 14 = T
Choose...
Choose...
Choose...
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