On New Perspectives for Statistical Computing in Business and Industry – A Solution with STATISTICA and R
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Christian H. Weiß
Abstract
Companies in business and industry often make very different demands on statistical software packages, like flexibility concerning customized solutions, possibility of integrating non-standard stochastic approaches, use to validated applications, user-friendly interface, moderate costs, and many more. Usually, it is not possible to find a single software package that satisfies all such demands. Therefore, it would be attractive for entrepreneurs and statistical consultants if a collaboration among statistical software packages (e.g., leading commercial package extended by open source system) could be realized easily.
In this article, we show how statistical procedures offered by R are easily integrated into the graphical user interface of STATISTICA, using the R DCOM Server of [Baier and Neuwirth, R/Scilab (D)COM Server V 3.0-1B5, 2008] and STATISTICA Visual Basic (SVB). We present solutions for different versions of STATISTICA, and illustrate all these approaches by an example from time series analysis: Using the tseries package of [Trapletti and Hornik, The tseries Package, Version 0.10-18, 2009], we tune STATISTICA with R by integrating R's ability for fitting GARCH models to given data into the user interface of STATISTICA.
© de Gruyter 2010
Artikel in diesem Heft
- Editorial
- Optimal Replacement Policy Based on the Number of Down Times
- An L-Banded Approximation to the Inverse of Symmetric Toeplitz Matrices
- Selection of Mixed Sampling Plans for Second Quality Lots
- On New Perspectives for Statistical Computing in Business and Industry – A Solution with STATISTICA and R
- Reliability Analysis of k-out-of-n : G Repairable Shared Load Systems with Multiple Failures and Preventive Maintenance
- Monitoring the Parameters of the Market Model by Linear Profile Procedures
- An Addendum to the Estimators of Murthy–Sarma and Anis–Pandey of the Mean of the Normal Distribution
- A Bounded Intensity Process Reliability Growth Model in a Bayes-Decision Framework
- Optimal Structure in Heterogeneous Multi-state Series-parallel Reliability Systems
Artikel in diesem Heft
- Editorial
- Optimal Replacement Policy Based on the Number of Down Times
- An L-Banded Approximation to the Inverse of Symmetric Toeplitz Matrices
- Selection of Mixed Sampling Plans for Second Quality Lots
- On New Perspectives for Statistical Computing in Business and Industry – A Solution with STATISTICA and R
- Reliability Analysis of k-out-of-n : G Repairable Shared Load Systems with Multiple Failures and Preventive Maintenance
- Monitoring the Parameters of the Market Model by Linear Profile Procedures
- An Addendum to the Estimators of Murthy–Sarma and Anis–Pandey of the Mean of the Normal Distribution
- A Bounded Intensity Process Reliability Growth Model in a Bayes-Decision Framework
- Optimal Structure in Heterogeneous Multi-state Series-parallel Reliability Systems
