ABSTRACT: This study examined the relationship between the Monetary Policy Rate (MPR) and inflation across five continents from 2014 to 2023 using both Frequentist and Bayesian Linear Mixed Models ...

Incrementality testing in Google Ads is suddenly within reach for far more advertisers than before. Google has lowered the barriers to running these tests, making lift measurement possible even ...

Bayesian methods for inference and prediction have become widespread in the social sciences (and beyond). Over the last decades, applied Bayesian modeling has evolved from a niche methodology with ...

While the majority of stroke researchers use frequentist statistics to analyze and present their data, Bayesian statistics are becoming more and more prevalent in stroke research. As opposed to ...

Abstract: The prediction step is a crucial element of the Bayesian recursion for target tracking and state estimation in general. Discrete representations of the probability density function (pdf) can ...

Copyright: © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Frequentist and Bayesian ...

Abstract: In this paper we present a Bayes inference model for a simple step-stress accelerated life test (SSALT) using type-II censored samples. We assume that the failure times at each stress are ...

Cite this article : Fakhfakh, M., Chaari, L. (2024). Bayesian optimization for sparse neural networks with trainable activation functions. IEEE Transactions on Pattern Analysis and Machine ...

We enhance the Bayesian Mendelian Randomization (MR) framework of Berzuini et al. (Biostatistics 21(1):86-101, 2018) by allowing for interval null causal hypotheses, where values of the causal effect ...