Limdep 11 kaufen
136.85

 

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inkl. 19 % USt

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136,85

LIMDEP ist eine Ökonometrie Software für Schätzung und Analyse mit linearen und nichtlinearen Modellen, Cross Over-, Zeitreihen und Paneldaten. LIMDEP beschäftigt sich seit langem mit ökonometrischen und statistischen Analysen und hat viele Innovationen einschließlich modernster Techniken u. a. in den Bereichen Paneldatenanalyse und Discrete Choice Modeling zur Verfügung gestellt.

Limdep findet verbreitet Anwendung in Forschung, Studium und Verwaltung.

Alleinstellungsmerkmal der Software ist die verarbeitbare Modellkomplexität, die im Wesentlichen nur durch praktische Modellüberlegungen, Arbeitsspeicher und Rechenzeit begrenzt ist. Es sind Logit-, Probit-, Tobit- und "discrete choice"-Modelle rechenbar. Neben Logistischer Regression ist ein weiterer Anwendungsbereich der Software die Zeitreihenanalyse. Für die Software Limdep gibt es ein Erweiterungsmodul mit Namen Nlogit.

Argumente für Limdep:

  • Wichtige Software für Zeitreihenanalyse
  • Innovativ bei der Paneldatenanalyse
  • Discrete Choice Modeling

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LIMDEP

LIMDEP ist ein integriertes Program zur Schätzung und Analyse linearer und nichtlinearer Modelle, Modelle mit "cross section", Modelle mit Zeitreihen und Moelle mit "panel data". LIMDEPs wichtigstes Merkmal ist sein Packet aus über 100 "built-in" Schätzern für alle Arten von linearen Regressionen, und stochastischen Grenzen, Discrete-Choice-Modellen und Modelle von begrenzt abhängigen Variablen, einschließlich Modelle für binäre, zensierte und angeschnittene, Lebensdauerdaten und Zähldatenvariablen, diskrete und stetige Variablen und eine Vielzahl von Modellen zur Auswahl von Stichproben. Keine andere Software ist so auf dem neuesten Stand, so schnell, genau und leicht zu benutzen und kein anderes Programm bietet einen weiteren Bereich von einfachen und multiplen linearen Gleichungen und nichtlinearen Modellen .

LIMDEP ist "State-Of-The-Art" Software, die weltweit tausendfach in Lehre und Forschung an Universitäten, Regierungsorganisationen, Forschungsinstituten und der Industrie verwendet wird.

Weitere Informationen

Systemvoraussetzungen für die Software Limdep

  Windows®
Andere Voraussetzungen DVD-ROM Laufwerk
Betriebssystem Windows XP, Vista, 7, 8, 10
Minimum CPU 486 Processor oder höher
Min. RAM 512 MB RAM
Festplattenplatz 100 MB freier Speicherplatz auf der Festplatte

Model Estimation and Analysis

Over 100 model formulations for continuous, discrete, limited and censored dependent variables are provided, including:

  • Linear and nonlinear regression
  • Robust estimation
  • Binary choice
  • Ordered choice models
  • Unordered multinomial choice
  • Censoring and truncation
  • Sample selection models
  • Count data
  • Loglinear models
  • Stochastic frontier and DEA
  • Survival analysis
  • Quantile regression (linear and count)
  • Time series models
  • Panel data models

Data Description and Graphics

Descriptive statistics and graphical analysis tools include:

  • Descriptive statistics for cross sections and panels
  • Tables of means and quantiles
  • Time series
  • Spectral density
  • Graphics tools
  • Kernel density
  • Discriminant analysis
  • Contour plots

Count Data

The widest range of specifications for count data of any package is provided, including several newly developed models:

  • Poisson and negative binomial models
  • New specifications for NB models
  • Gamma, generalized Poisson, Polya-Aeppli
  • Zero inflation and hurdle
  • Fixed and random effects
  • Latent class
  • Quantile Poisson regression

Data Environments

Nearly every model may be extended to a variety of frameworks including:

  • Data transformations
  • Multiple imputation
  • Cross section
  • Panel data
  • Time series manipulation

Programming and Numerical Analysis

Programming language including matrix and data manipulation commands is provided for building new estimators:

  • MAXIMIZE/MINIMIZE for user supplied functions
  • Matrix programming with LIMDEP
  • Scientific calculator
  • Numerical analysis tools, integration and differentiation
  • Simulation based estimation
  • Program Gibbs samplers

Frontier and Efficiency Analysis

All forms of the stochastic frontier model are provided:

  • Fixed and random effects
  • True fixed and random effects
  • Latent class stochastic frontier
  • Battese and Coelli
  • Heteroscedasticity
  • Technical inefficiency estimation
  • Data envelopment analysis (This is the only package with both SFA and DEA.)

Discrete Choice Models in LIMDEP

Discrete choice estimators for binary, multinomial, ordered, count and multivariate discrete data are provided:

  • Binary choice - dozens of specifications
  • Ordered choice
  • Hierarchical ordered choice
  • Panel data
  • Multinomial logit
  • Count data models
  • Bivariate binary and ordered choice
  • Discrete choice with sample selection

Time Series Analysis

A range of estimators for time series are provided including:

  • ARMAX models
  • GARCH and GARCH-in-mean models
  • Spectral density estimation
  • ACF and PACF
  • Phillips-Perron tests
  • Newey-West estimator

Accuracy

Extremely accurate computational methods are employed throughout. High marks are earned on all National Institute of Standards and Technology test problems, including:

  • Descriptive statistics
  • Analysis of variance
  • Linear regression
  • Nonlinear least squares

Post Estimation

Extensive tools for post estimation enable manipulation of model results along with other statistics and procedures.

Data Management

Data management tools are provided for input of data or internal generation with the random number generators, including:

  • Data transformations
  • Sampling and bootstrapping
  • Bootstrap cross section observations or panel groups
  • Weighted data
  • Random number generation
  • Cluster sampling and stratification

Multiple Imputation

Multiple Imputation is used to generate proxies for missing values in order to use information from the model and within the sample to increase the precision of estimators. Missing values for continuous, binary, count, Likert, fractional and multinomial data may be generated. Results from multiple samples are generated and averaged to produce the final results.

What's New in LIMDEP 10?

Version 10 contains major new extensions to the program for estimation and analysis of econometric models and a long list of new models and features.

Model Estimation, Analysis and Simulation

  • Interactions and Nonlinearities: Models that contain interactions, products, powers and logs of variables are now specified explicitly. The basic command structure is fully integrated throughout the entire program, not just layered on top of a few models. Every specification of every model can use this structure. This will provide a significant convenience in the specification of models. But, the major benefit of this explicit format comes in terms of how it enables you to obtain partial effects and simulations for your models.
  • Partial Effects: Partial effects, using the sample averages of the effects or calculations at the means of the data, can be computed automatically for any variable in any model regardless of how intricate. Effects can be simulated for specified values or ranges of variables, and tabulated or plotted with confidence intervals. The lack of appropriate calculations of partial effects for models that contain interactions and nonlinearities has been recognized as a major shortcoming of software and of many published analyses. LIMDEP's new PARTIAL EFFECTS command solves this problem. This feature can be used with all models fit by LIMDEP, or with a function of your own that need not be part of any built in model in the program. This feature will change the way you analyze nonlinear models.
  • Model Simulation and Oaxaca Decomposition: The partial effects feature can also be used to simulate the prediction function (usually the conditional mean) for any model fit by LIMDEP, or any model or equation that you wish to specify in the SIMULATE command. Simulations can involve scenarios, such as tracing the sample average prediction of a probability or a count of outcomes as a function of age. The simulation feature is also useful for computing Oaxaca decompositions for subgroups of the sample. Like PARTIAL EFFECTS and SIMULATE, DECOMPOSE is used with all models built into LIMDEP, or with a function or model that you specify yourself.
  • Multiple Imputation: The technique of multiple imputation for handling missing data has been gaining popularity. LIMDEP's new implementation of this technique is woven into the entire program, not just a few specific models. Any estimator, even your own created with MAXIMIZE, or any other computation involving data that produces a coefficient vector and a sampling covariance matrix, can be based on multiple imputed data sets. And, we have built this technique to bypass the need to create multiple data sets - traditionally, the need to replicate the full data set has hobbled this method. LIMDEP's implementation of multiple imputation uses only the existing data set. The results are fully replicable as well. (You can create and save the imputed data sets if you wish.)

Extensions of Estimation and Analysis Methods

  • Streamlined output with additional test and diagnostic statistics
  • Restrictions and hypothesis tests in all models
    • Simpler natural format for model specification
    • Single step estimation for testing multiple hypotheses
  • Numerous new features for user written iterative and looping procedures
  • New Wald features for computing standard errors
    • Sample average functions as an alternative to computing functions at the means of the data
    • Variances using the delta method account for the averaging procedure
  • Multiple new functions for matrix algebra program
  • Expanded graphics capabilities
    • New additions for kernel density estimation, including plotting multiple KDEs in the same figure
    • Contour plots
    • Enhanced tools for creating and labeling graphs
  • Robust covariance estimators for linear models
  • Jackknife and bootstrap estimators for standard errors and confidence intervals and for large sample behavior of test statistics
  • Extension of panel data to nearly all model frameworks

New Models and Data Analysis Settings

  • Models for count data
    • Zero truncation for count data models with panel data
    • NB-X - negative binomial model for underdispersion
    • NB-E - negative binomial model with endogenous truncation (on site sampling)
    • Poisson and negative binomial models with endogenous treatment effects
    • Poisson - inverse gauss mixture
    • Generalized Poisson with zero inflation and 1/2/P nested functional forms
    • Count data hurdle models with endogenous participation
  • Non- and semiparametric regression models
    • Lowess nonparametric regression
    • QREG for quantile regression
    • QCREG for quantile regression for count data
  • LIML estimator for regression with endogenous RHS variables
  • Binary and ordered choice
    • Ordered probit with endogenous treatment effects
    • Generalized ordered choice with random parameters and thresholds
    • Fractional response model for panel data
    • Arc tangent model for binary choice
  • Stochastic frontier
    • FRONTIER with nonparametric frontier function
    • Battese-Coelli panel data frontier models
    • New automated tools for specification tests and calculations such as technical efficiencies
  • MAXIMIZE/MINIMIZE with random parameters
  • Numerical Analysis
    • FUNCTION to plot and simulate any specified function
    • SOLVE to locate the solutions to f(x)=0

Program Limits at a Glance

We are often asked about LIMDEP's specific internal limits. The following limits are relevant to the most common applications.

  • Active Data Set
    • Variables: 900
    • Observations: 3,000,000+
    • Total cells in data area: limited by memory
    • Namelists: 25
    • Variables in namelist: 100
  • Command Entry
    • Characters in one command: 10,000
    • Characters in a stored procedure: 10,000
    • Commands in a stored procedure: 100
    • Stored procedures: 10
  • Model Size, General & Specific
    • Number of parameters: 150
    • Equations for SURE & 3SLS: 30
    • Equations for WALD, NLSURE, GMM: 50
  • Panel Data Models
    • Groups in fixed & random effects:
      • Linear models: unlimited
      • Nonlinear models: 100,000
    • Regressors in fixed & random effects: 150
    • Periods in linear effects: 1,000
    • Groups x Regressors: unlimited
    • Periods in fixed effects (Chamberlain) logit: 100
  • Matrix & Scalar Algebra
    • Number of active matrices: 100
    • Number of active named scalars: 100
    • Size of a matrix: 50,000 cells

LIMDEP 10 Documentation

The LIMDEP 10 documentation with over 2,500 pages, contains full reference guides for the program, background econometrics, and sample applications. The LIMDEP documentation consists of two guides:

LIMDEP 10 Reference Guide

The LIMDEP 10 Reference Guide provides all instructions for operating the program, including installation, invocation, and most of the basic setup operations that precede model estimation. These operations include reading and transforming data and setting the sample. This manual also describes the optimization procedures, how to use the matrix algebra package and scalar scientific calculator as stand alone tools and as part of LIMDEP programs, what types of results are produced by the program, and some of the common features of the model estimation programs, such as how to do post estimation analysis of model results, including partial effects and simulation. The LIMDEP Reference Guide also includes a complete listing of the program diagnostics.

LIMDEP 10 Econometric Modeling Guide

The LIMDEP 10 Econometric Modeling Guide provides the econometric background, LIMDEP commands, and examples with data, commands and results. Topics are arranged by modeling framework, not by program command. There are chapters on

  • Descriptive statistics
  • Linear regression
  • Panel data analysis
  • Heteroscedasticity
  • Binary choice models
  • Models for count data
  • Censored and truncated data
  • Survival models
  • Nonlinear regression
  • Time series models
  • Nonlinear optimization
  • Sample selection models

and many others. Each model fit by the program is fully documented. The full set of formulas for all computations are shown with complete mathematical documentation of the models. Additional chapters in this guide show how to do numerical analysis and how to program your own estimators.