User:Amatdiou/Books/Regression analysis

Regression analysis

 * Category:Regression analysis
 * Outline of regression analysis
 * Regression analysis
 * Additive model
 * Antecedent variable
 * Autocorrelation
 * Backfitting algorithm
 * Bayesian linear regression
 * Bayesian multivariate linear regression
 * Calibration (statistics)
 * Canonical analysis
 * Causal inference
 * Censored regression model
 * CHAID
 * Coefficient of determination
 * Comparison of general and generalized linear models
 * Component analysis (statistics)
 * Compressed sensing
 * Conditional change model
 * Controlling for a variable
 * Cross-sectional regression
 * Curve fitting
 * Deming regression
 * Dependent and independent variables
 * Design matrix
 * Difference in differences
 * Dummy variable (statistics)
 * Elastic net regularization
 * Errors and residuals in statistics
 * Errors-in-variables models
 * Explained sum of squares
 * Explained variation
 * Factor regression model
 * First-hitting-time model
 * Fixed effects model
 * Fraction of variance unexplained
 * Frisch–Waugh–Lovell theorem
 * General linear model
 * Generalized estimating equation
 * Generalized least squares
 * Generalized linear model
 * Growth curve
 * Guess value
 * Hat matrix
 * Heckman correction
 * Heteroscedasticity-consistent standard errors
 * Hierarchical generalized linear model
 * Hosmer–Lemeshow test
 * Influential observation
 * Instrumental variable
 * Interaction (statistics)
 * Isotonic regression
 * Iteratively reweighted least squares
 * Kitchen sink regression
 * Lack-of-fit sum of squares
 * Least squares
 * Leverage (statistics)
 * Limited dependent variable
 * Linear least squares (mathematics)
 * Linear model
 * Linear regression
 * Local regression
 * Mallows's Cp
 * Mean and predicted response
 * Meta-regression
 * Mixed model
 * Moderated mediation
 * Moderation (statistics)
 * Moving least squares
 * Multicollinearity
 * Multinomial logistic regression
 * Multinomial probit
 * Multiple correlation
 * Multivariate adaptive regression splines
 * Multivariate probit model
 * Newey–West estimator
 * Non-linear least squares
 * Nonlinear regression
 * Nonparametric regression
 * Omitted-variable bias
 * Optimal design
 * Ordered logit
 * Ordinal regression
 * Ordinary least squares
 * Overfitting
 * Partial least squares regression
 * Partition of sums of squares
 * Path analysis (statistics)
 * Path coefficient
 * Poisson regression
 * Policy capturing
 * Polynomial and rational function modeling
 * Polynomial regression
 * Prediction interval
 * Principal component regression
 * Principle of marginality
 * Probit model
 * Projection pursuit regression
 * Proofs involving ordinary least squares
 * Propensity score matching
 * Proper linear model
 * Proportional hazards model
 * Pyrrho's lemma
 * Quantile regression
 * Radial basis function network
 * Random multinomial logit
 * Regression dilution
 * Regression model validation
 * Regression toward the mean
 * Residual sum of squares
 * Robust regression
 * Savitzky–Golay filter for smoothing and differentiation
 * Scatterplot smoothing
 * Seemingly unrelated regressions
 * Segmented regression
 * Semiparametric regression
 * Separation (statistics)
 * Simple linear regression
 * Sinusoidal model
 * Sliced inverse regression
 * Smearing retransformation
 * Smoothing spline
 * Sobel test
 * Specification (regression)
 * Standardized coefficient
 * Stepwise regression
 * Structural equation modeling
 * Tobit model
 * Total least squares
 * Total sum of squares
 * Trend analysis
 * Truncated regression model
 * Unit-weighted regression
 * Variable rules analysis
 * Virtual sensing
 * Zero-inflated model


 * Category:Choice modelling
 * Choice modelling
 * Discrete choice
 * MaxDiff
 * Preference regression
 * Preference-rank translation


 * Category:Generalized linear models
 * Binomial regression
 * Generalized additive model
 * Generalized additive model for location, scale and shape
 * Generalized linear array model
 * Generalized linear mixed model
 * Linear probability model


 * Category:Least squares
 * Discrete least squares meshless method
 * Gauss–Newton algorithm
 * Least squares (function approximation)
 * Least squares support vector machine
 * Levenberg–Marquardt algorithm
 * Mean squared error
 * Non-linear iterative partial least squares
 * Numerical smoothing and differentiation


 * Category:Nonparametric regression
 * Category:Statistical outliers
 * Outlier
 * Anomaly detection
 * Box plot
 * Chauvenet's criterion
 * Cook's distance
 * Dixon's Q test
 * Grubbs' test for outliers
 * Local outlier factor
 * Outliers ratio
 * Peirce's criterion
 * RANSAC
 * Studentized residual


 * Category:Regression and curve fitting software
 * CumFreq
 * DataScene
 * Fityk
 * GraphPad Prism
 * Gretl
 * IGOR Pro
 * LabPlot
 * MagicPlot
 * Mathematica
 * Origin (software)
 * PeakFit
 * QtiPlot
 * Regression Analysis of Time Series
 * SegReg
 * SHAZAM (software)
 * SimFiT
 * TableCurve 2D


 * Category:Regression diagnostics
 * Breusch–Godfrey test
 * Breusch–Pagan test
 * Chow test
 * DFFITS
 * Goldfeld–Quandt test
 * Park test
 * Partial leverage
 * Partial regression plot
 * Partial residual plot
 * Portmanteau test
 * PRESS statistic
 * Ramsey RESET test
 * Regression diagnostic
 * Variance inflation factor
 * White test


 * Category:Regression variable selection
 * Akaike information criterion
 * Bayesian information criterion
 * Cross-validation (statistics)
 * Deviance information criterion
 * Focused information criterion
 * Freedman's paradox
 * Group method of data handling
 * Hannan–Quinn information criterion
 * Least-angle regression
 * Model selection


 * Category:Nonparametric regression
 * Category:Regression with time series structure
 * Cochrane–Orcutt estimation
 * Prais–Winsten estimation
 * Time-series regression
 * Unit root


 * Category:Robust regression
 * Least absolute deviations
 * Least trimmed squares
 * M-estimator
 * Theil–Sen estimator