Autoregressive models predict future values using past data patterns. Discover how these models work and their application in ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Written by a prominent statistician and author, the first edition of this bestseller broke new ground in the then emerging subject of spatial statistics with its coverage of spatial point patterns.

CATALOG DESCRIPTION: Fundamental and advanced topics in statistical pattern recognition including Bayesian decision theory, Maximum-likelihood and Bayesian estimation, Nonparametric density estimation ...

Change a single number in a math problem, and a human who understands the underlying logic will still get the right answer.

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

Researchers at the University of Oregon have developed the first language model for population genetics, capable of tracing gene pairs back to their last common ancestor in minutes. Trained on ...

The feedback loops that define DeFi, on-chain contagion, and crypto financial crime are not statistical phenomena. They are causal ones. The industry's modelling infrastructure has not caught up. On 9 ...

Researchers at the University of Oregon have developed an artificial intelligence tool that can read genetic code the way large language models like ChatGPT read text. Scanning the genome for ...