v0.8.0

• cap too large gradient descent steps on log-scale for covariance parameters, GLMMs: reset small learning rates for covariance parameters and regression parameters if the other parameters change
• add gaussian_neg_log_likelihood as validation metric
• add function ‘get_nested_categories‘ for nested grouped random effects
• prediction: remove nugget variance from predictive (co)variances when predict_response = false for Gaussian likelihoods
• set default value for predict_response to true in prediction function of GPModel
• NA’s and Inf’s are not allowed in label
• correct prediction if Vecchia approximation for non-Gaussian likelihoods