Econometrics

Econometrics provides functions for modeling economic data. Econometrics Toolbox selects and calibrates economic models for simulation and forecasting. Matlab tool provides functions for data modeling in econometrics. It also provides methods for modeling economic systems using state-space models and for estimating using the Kalman filter. Experts at Matlab Homework Experts toil to guide the students in Econometrics help in the most appropriate way. We have the ability to deal with all kinds of topics under Econometrics. Our Econometrics experts and tutors are available 24/7 for your help. They provide in-depth Econometrics solution. We assure to deliver highest quality Econometrics assignment solution within the deadline. Our Econometrics Matlab Experts will help you to sort out all the tiny or major problems.

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  • Model Identification and Analysis
  • State-Space Modeling and Parameter Estimation
  • Co-integration Modeling
  • Regression Diagnostics
  • VAR and Error Correction Models
  • Limited Dependent Variable Models
  • Regression using MATLAB
    • Design of the regression library
    • Selecting a least-squares algorithm
    • Performance profiling the regression toolbox
  • Simultaneous Equation Models
    • Two-stage least-squares models
    • Three-stage least-squares models
    • Seemingly unrelated regression models
  • Utility Functions
    • Calendar function utilities
    • Printing and plotting matrices
    • Data transformation utilities
    • Gauss & Wrapper functions
  • Optimization functions library
    • Simplex optimization
    • Univariate & Multivariate simplex optimization
    • EM algorithms for optimization
    • Multivariate gradient optimization
  • Markov Chain Monte Carlo Models
    • The Bayesian Regression Model
    • The Gibbs Sampler
    • Monitoring convergence of the sampler
    • Autocorrelation estimates
    • Raftery-Lewis diagnostics
  • Distribution functions library
    • The pdf, cdf, inv and rnd functions
    • The specialized functions
  • Handling sparse matrices
    • Computational savings with sparse matrices
    • Estimation using sparse matrix algorithms
    • Gibbs sampling and sparse matrices