REFERENCE

  1. GAUSS Quick Reference
  2. MATRIX manipulation
  3. Relational and logical operators
  4. The Source Path (SRC_PATH)

GAUSS BASICS

  1. Getting Started with GAUSS
  2. Beginner program: Nearest neighbor search
  3. Generating data from a linear model
  4. Viewing Data in GAUSS
  5. Graphing data

VIDEO SERIES 

  1. Interactive commands
  2. Running a program
  3. Introduction to matrices
  4. Matrix operations
  5. Element-by-element conformability
  6. Logical and relational operators

LOADING DATA

  1. Reading and writing Excel data with GAUSS
  2. Reading CSV and other text data
  3. Loading variables from Excel into GAUSS
  4. Saving and loading GAUSS matrix files

GRAPHING IN GAUSS

  1. Basic graphs in GAUSS with programmatic customization
  2. Exporting graphs interactively
  3. Time series plots

OPTIMIZING YOUR GAUSS CODE

  1. Vectorizing GAUSS Programs
  2. Loop Optimizations

THREADING IN GAUSS

  1. Introduction: Internally threaded functions
  2. User created threads
  3. Performance considerations
  4. Introduction to Parallel loops

USING STRUCTURES

  1. Why learn to use structures?
  2. A gentle introduction to using structures
  3. Converting to structures: An example with ols and olsmt

MULTI-DIMENSIONAL ARRAYS IN GAUSS

  1. Multi-dimensional array basics in GAUSS

FORMULA STRING SYNTAX 

  1. Descriptive statistics with a formula string
  2. Ordinary least squares regression with a formula string
  3. Generalized linear model with a formula string

ECONOMETRICS BASICS IN GAUSS 

  1. Linear regression
  2. Generating and visualizing regression residuals
  3. OLS diagnostics: Error term normality
  4. OLS diagnostics: Heteroscedasticity
  5. OLS diagnostics: Influential data tests
  6. OLS diagnostics: Multicollinearity
  7. OLS diagnostics: Model specification

GENERALIZED METHOD OF MOMENTS (GMM) 

  1. Introduction and basic usage
  2. User-defined moment equations
  3. GMM control settings
  4. GMM Application: OLS estimation with exogenous regressors
  5. GMM Application: OLS estimation with endogenous regressors

BAYESIAN FUNDAMENTALS

  1. Monte Carlo integration
  2. Importance sampling
  3. Gibbs sampling from a bivariate normal distribution
  4. Metropolis-Hastings sampler

TIME SERIES ANALYSIS 

  1. Introduction to TSMT and basic usage
  2. Simulating ARMA data
  3. Finding The Sample ACF and PACF
  4. Estimating ARIMA Models
  5. U.S. Whole Sale Price Index Application: Visualizing Time Series Data
  6. Filtering data with the Kalman Filter

QUANTILE REGRESSION 

  1. Introduction to quantile regression
  2. Specifying the quantile levels
  3. Performing weighted analysis
  4. Storing output from quantile regressions
  5. The qFitControl structure
  6. Changing variable names for quantile regression
  7. Specifying printing options for quantile regression
  8. Standard errors and confidence intervals for quantile regression