… We can extract the coefficients and make predictions for a glmnet object at certain … t-statistic
with groups defined by y. Again, we present an efficient function for computing the t-statistics, …

… To statistically infer QTNs, we formulated the student’s t statistic based on generalized linear
models for the normally distributed and binary traits, or Cox proportional hazard model for …

… A comparison and evaluation of the six developed SVR models and the proposed SVRs–GLMNET
model were implemented based on five statistical criteria, such as mean absolute …

… AOp prediction (Bui et al. 2019a, b, c, d). Although the GLMNET model was introduced earlier
for AOp prediction, it … In this study, the GLMNET model was also applied to predict AOp but …

… glmnet … .glmnet function is a convenience function that runs CV for the λ tuning parameter.
The returned object has class " cv.glmnet ", which comes equipped with plot, coef and predict …

… There are large numbers of statistical models for genomic prediction available in the …
prediction. This study will help researcher in selection of appropriate statistical method to predict …

… Data from a total of 131 patient encounters from 42 patients in a clinical remission were
included in the study to develop the statistical model (Table 2). 31(75.6%) were White and 10 (…

… learning-based prediction models (ie Glmnet, RF, XGBoost, LightGBM) to commonly used
regression models for prediction of undiagnosed … Statistical analysis and model validation …

… model M3) implemented in the library glmnet, and the support vector machine (… statistical
differences between the four models in terms of prediction performance, but the best predictions …

… algorithms (GLMNET and Random Forest) applied for modelling and predicting fire behavior
(… In our study, the statistical analysis was conducted using the R software (R CORE TEAM, …