Description Usage Arguments Details Value References Examples
This function calculates the maximum likelihood for binary logistic regression via the Newton Raphson algorithm.
1 | newtonRaphson(y, X, precision = 1e-07, iterMax = 25)
|
y |
Matrix/vector containing the response variable. |
X |
Matrix/vector containing the design matrix (including intercept). |
precision |
Degree of precision of algorithm. |
iterMax |
Maximum number of iterations of optimisation algorithm. |
This algorithm is used on the logitModel
regression estimation
function.
A list with maximum likelihood estimation results for further computation.
Agresti, A (2013) Categorical Data Analysis, John Wiley & Sons, 2013, Volume 792 of Wiley Series in Probability and Statistics, ISSN 1940-6517
Czepiel, S.A. (2002) Maximum Likelihood Estimation of Logistic Regression Models: Theory and Implementation. Available at czep.net/stat/mlelr.pdf. [visited: 25.03.2018]
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