Search Results - Probability Theory and Statistical Modeling

Probability theory and statistical inference : econometric modeling with observational data by Spanos, Aris

“…This major textbook is intended for students taking introductory courses in Probability Theory and Statistical Inference…”
Get full text

Probability theory and statistical inference: econometric modeling with observational data by Spanos, Aris

“…This major textbook from a distinguished econometrician is intended for students taking introductory courses in probability theory and statistical inference…”
Get full text

Probability Theory and Statistical Inference: Econometric Modeling with Observational Data by Spanos, Aris

“…This major textbook from a distinguished econometrician is intended for students taking introductory courses in probability theory and statistical inference…”
Get full text

Computational and Statistical Innovations in Structural Failure Analysis: Sprain Energy Theory and Fishnet Probability Modeling by Xu, Houlin

“…Ensuring structural safety at a target failure probability below 10-6 remains a key challenge in modern engineering…”
Get full text

A Statistical Method for Empirical Testing of Competing Theories by Imai, Kosuke, Tingley, Dustin

“… of multiple statistical models under consideration. Researchers can then estimate the probability that a specific observation is consistent with each rival theory…”
Get full text

Statistical modeling of joint probability distribution using copula: Application to peak and permanent displacement seismic demands by Goda, K.

“… tool for modeling and simulating nonlinearly-interrelated data. In this study, an introduction as well as illustrative application of the copula theory is given in the context of structural reliability…”
Get full text

An information-theoretic approach to the modeling and analysis of whole-genome bisulfite sequencing data by Jenkinson, Garrett, Abante, Jordi, Feinberg, Andrew P., Goutsias, John

“… Statistical modeling and analysis is employed to computationally extract and quantify information from these profiles in an effort to identify regions of the genome that demonstrate crucial…”
Get full text

Mixed Skewness Probability Modeling and Extreme Value Predicting for Physical System Input/Output Based on Full Bayesian Generalized Maximum-Likelihood Estimation by Zhang, Xiaonan, Ding, Youliang, Zhao, Hanwei, Yi, Letian, Guo, Tong, Li, Aiqun, Zou, Yang

“…Dynamic parameterization of the statistical characteristics of structural systems' measured input and output data is an important task for the digital twin modeling and intelligent risk assessment…”
Get full text

Probability theory and statistical inference: econometric modeling with observational data by Spanos, Aris

“…This major new textbook is intended for students taking introductory courses in Probability Theory and Statistical Inference…”
Get full text

Bayesian structural equation modeling: a more flexible representation of substantive theory by Muthén, Bengt, Asparouhov, Tihomir

“…This article proposes a new approach to factor analysis and structural equation modeling using Bayesian analysis…”
Get more information

Toward Sustainable Water Infrastructure: The State‐Of‐The‐Art for Modeling the Failure Probability of Water Pipes by Taiwo, Ridwan, Ben Seghier, Mohamed El Amine, Zayed, Tarek

“…) by providing (a) a bibliometric analysis of existing scholarly literature, (b) a systematic review of the techniques used in modeling the failure probability of water pipes…”
Get full text

Advances in statistical modeling of spatial extremes by Huser, Raphaël, Wadsworth, Jennifer L.

“…The classical modeling of spatial extremes relies on asymptotic models (i.e., max‐stable or r‐Pareto processes) for block maxima or peaks over high thresholds, respectively…”
Get full text

Unsupervised Generative Modeling Using Matrix Product States by Han, Zhao-Yu, Wang, Jun, Fan, Heng, Wang, Lei, Zhang, Pan

“…Generative modeling, which learns joint probability distribution from data and generates samples according to it, is an important task in machine learning and artificial intelligence…”
Get full text

Understanding Probability Models by Bouza-Herrera, Carlos Narciso

“…"This book intends to highlight how the Theory of Probability supports, not only statistical modeling but how it allows describing different real life phenomena…”
Get full text

Linking statistical and hydrodynamic modeling for compound flood hazard assessment in tidal channels and estuaries by Moftakhari, Hamed, Schubert, Jochen E., AghaKouchak, Amir, Matthew, Richard A., Sanders, Brett F.

“…•Compound flood hazard levels computed for tidal channels or estuaries.•Bivariate statistical and hydrodynamic modeling is linked…”
Get full text

Features of the assessment of occupational risks under hazardous working conditions by Golinko, V. I, Zabelina, V. A

“… Theoretical studies are based on the use of the basic provisions of probability theory, methods of mathematical modeling, statistical processing of indicators of occupational morbidity and methods…”
Get full text

Nonparametric Bayes Modeling of Populations of Networks by Durante, Daniele, Dunson, David B., Vogelstein, Joshua T.

“… are collected for each patient under study, motivating statistical models which can flexibly characterize…”
Get full text

A theory of states and traits--revised by Steyer, Rolf, Mayer, Axel, Geiser, Christian, Cole, David A

“… States and traits are defined in terms of probability theory. This allows for a seamless transition from theory to statistical modeling of empirical data…”
Get more information

Probability state modeling theory by Bagwell, C. Bruce, Hunsberger, Benjamin C., Herbert, Donald J., Munson, Mark E., Hill, Beth L., Bray, Chris M., Preffer, Frederic I.

“… Probability state modeling (PSM) is a technique that addresses both of these issues. The theory and important algorithms associated with PSM are presented along with simple examples and general strategies for autonomous analyses…”
Get full text

Spatial modeling with R‐INLA: A review by Bakka, Haakon, Rue, Håvard, Fuglstad, Geir‐Arne, Riebler, Andrea, Bolin, David, Illian, Janine, Krainski, Elias, Simpson, Daniel, Lindgren, Finn

“…Coming up with Bayesian models for spatial data is easy, but performing inference with them can be challenging. Writing fast inference code for a complex…”
Get full text