the aim of this study was to investigate the potential association between growth hormone gh/alui and growth hormone receptor ghr/alui polymorphisms with milk yield and reproductive performances in holstein dairy cows in iran. blood samples of 150 holstein cows were collected and their genomic dna was extracted using gene-fanavaran dna extracting kit. fragments of the 428 bp of exon 5 growth ho...

Logistic regression is a technique to map the input feature to the posterior probability for a binary class. The optimal parameter of regression function is obtained by maximizing log likelihood of training data. In this report, we implement two optimization techniques 1) stochastic gradient decent (SGD); 2) limited-memory BroydenFletcherGoldfarbShanno (L-BFGS) to optimize the log likelihood fu...

Multiple Logistic Regression Just as in OLS regression, logistic models can include more than one predictor. The analysis options are similar to regression. One can choose to select variables, as with a stepwise procedure, or one can enter the predictors simultaneously, or they can be entered in blocks. Variations of the likelihood ratio test can be conducted in which the chi-square test (G) is...

Logistic regression is the most common method used to model binary response data. When the response is binary, it typically takes the form of 1/0, with 1 generally indicating a success and 0 a failure. However, the actual values that 1 and 0 can take vary widely, depending on the purpose of the study. For example, for a study of the odds of failure in a school setting, 1 may have the value of f...

This paper considers logistic regression analysis with linked data. It is shown that, in logistic regression analysis with linked data, a finite mixture of Bernoulli distributions can be used for modeling the response variables. We proposed an iterative maximum likelihood estimator for the regression coefficients that takes the matching probabilities into account. Next, the Bayesian counterpart...