Factor Analysis
This reference manual section covers NumXL's Factor Analysis functions, including principal components analysis (PCA), least-squares regression, generalized linear models, and other related methods.
- Generalized Linear Model
- GLM - GLM Model Definition
- GLM_AIC - Akaike's information criterion (AIC) of the GLM Model
- GLM_CALIBRATE - GLM Parameters' Calibration
- GLM_CHECK - Verify GLM Parameters' Values
- GLM_ERRORS - GLM Parameters' Standard Errors
- GLM_FORE - GLM Forecast
- GLM_FORECI - GLM Forecasting Confidence Interval
- GLM_FORESD - GLM Forecast Error
- GLM_GUESS - Initial Values of GLM Model's Parameters
- GLM_LLF - GLM Log Likelihood Function
- GLM_MEAN - GLM Fitted Values
- GLM_RESID - GLM Residuals Time Series
- GLM_RSQ - R-Squared of GLM Model
- GLM_VOL - Standard Deviations of the GLM Residuals
- Simple Linear Regression (SLR) Model
- SLR_PARAM - Simple Regression Coefficients Values
- SLR_GOF - Goodness of fit for Simple Regression Model
- SLR_FITTED - Simple Linear Regression Fitted Values
- SLR_FORE - Forecasting for Simple Linear Regression Model
- SLR_ANOVA - Simple Regression Analysis of Variance (ANOVA)
- Multiple Linear Regression Model
- MLR_ANOVA - Regression Analysis of Variance (ANOVA)
- MLR_FORE - Forecasting for Linear Regression Model
- MLR_FITTED - Linear Regression Fitted Values
- MLR_PARAM - Multiple Linear Regression Coefficients Values
- MLR_GOF - Goodness of fit of Linear Regression Model
- MLR_PRFTest - Partial f-test for Regression Variables
- MLR_STEPWISE - Regression Variables Selection Method (Stepwise)
- Principal Component Analysis