'Log linear models' diaporamas de présentation

Chapter 2: Data Preprocessing

Chapter 2: Data Preprocessing. Why preprocess the data? Data cleaning Data integration and transformation Data reduction Discretization and concept hierarchy generation Summary. Data Reduction Strategies. Why data reduction? A database/data warehouse may store terabytes of data

931 views • 73 slides

Chapter 2: Data Preprocessing

Chapter 2: Data Preprocessing. Why preprocess the data? Data cleaning Data integration and transformation Data reduction Discretization and concept hierarchy generation Summary. Data Reduction Strategies. Why data reduction? A database/data warehouse may store terabytes of data

1.41k views • 73 slides

Chapter 2: Data Preprocessing

Chapter 2: Data Preprocessing. Why preprocess the data? Data cleaning Data integration and transformation Data reduction Discretization and concept hierarchy generation Summary. Data Reduction Strategies. Why data reduction? A database/data warehouse may store terabytes of data

788 views • 73 slides

Statistical Disclosure Limitation: Releasing Useful Data for Statistical Analysis

Statistical Disclosure Limitation: Releasing Useful Data for Statistical Analysis. Stephen E. Fienberg Department of Statistics Center for Automated Learning & Discovery Center for Computer & Communications Security Carnegie Mellon University Pittsburgh, PA, U.S.A.

581 views • 49 slides

Statistical Disclosure Limitation: Releasing Useful Data for Statistical Analysis

Statistical Disclosure Limitation: Releasing Useful Data for Statistical Analysis. Stephen E. Fienberg Department of Statistics Center for Automated Learning & Discovery Center for Computer & Communications Security Carnegie Mellon University Pittsburgh, PA, U.S.A.

494 views • 49 slides

Discrete Multivariate Analysis

Discrete Multivariate Analysis. Analysis of Multivariate Categorical Data. References. Fienberg, S. (1980), Analysis of Cross-Classified Data , MIT Press, Cambridge, Mass. Fingelton, B. (1984), Models for Category Counts , Cambridge University Press.

581 views • 44 slides

Allowing Access to Confidential Data: Some Recent Experiences and Statistical Approaches

Allowing Access to Confidential Data: Some Recent Experiences and Statistical Approaches. Stephen E. Fienberg Department of Statistics Center for Automated Learning & Discovery Center for Computer & Communications Security Carnegie Mellon University Pittsburgh, PA, U.S.A. Overview.

443 views • 36 slides

General

Books on categorical data analysis (log-linear, logit, etc.), count data analysis, and life history analysis. General.

474 views • 27 slides

Statistical Methods

221 views • 20 slides

Parameter Learning in Markov Nets

Parameter Learning in Markov Nets. Dhruv Batra , 10-708 Recitation 11/13/ 2008. Contents. MRFs Parameter learning in MRFs IPF Gradient Descent HW5 implementation. Semantics. Priors on edges Ising Prior / Potts Model Metric MRFs. Metric MRFs. Energies in pairwise MRFs. HW4.

241 views • 15 slides

Sociology 690

Sociology 690. Multivariate Analysis Log Linear Models. IV DV. Category. Quantity. 1) Analysis of Variance Models (ANOVA). 2) Structural Equation Models (SEM). Quantity. Linear Models. Category. 3) Log Linear Models (LLM). 4) Logistic Regression Models (LRM). Category Models.

270 views • 14 slides

Multivariate analysis

University of Warwick, Department of Sociology, 2012/13 SO 201: SSAASS (Surveys and Statistics) (Richard Lampard ) Week 2 Multivariate analysis. Multivariate analysis.

150 views • 12 slides

Binary and binomial responses

Binary and binomial responses. The response probabilities are modelled as functions of the predictors Link functions: the probit link: the logit link: the log-log link:. Binary and binomial responses. the probit link: the logit link: the log-log link:. Link functions.

252 views • 11 slides

Count data, contingency tables and log-linear models

Count data, contingency tables and log-linear models. Expected frequency: Log-linear models are linear models of the log expected frequency (log is used as link function). A log-linear model for independence. The last parameter of each kind can be set to zero.

322 views • 10 slides

Shared Features in Log-Linear Models

Representation. Probabilistic Graphical Models. Template Models. Shared Features in Log-Linear Models. Ising Models. In most MRFs, same feature and weight are used over many scopes. Ising Model. same weight for every adjacent pair. Natural Language Processing.

163 views • 6 slides

Researches are necessary to a country

Vanward Statistics offers Statistical consulting service to businesses, doctoral students, the general public, and to researchers in various fields.

105 views • 6 slides