Search results for "jel:C13"

showing 6 items of 6 documents

Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs

2014

We develop an algorithm that incorporates network information into regression settings. It simultaneously estimates the covariate coefficients and the signs of the network connections (i.e. whether the connections are of an activating or of a repressing type). For the coefficient estimation steps an additional penalty is set on top of the lasso penalty, similarly to Li and Li (2008). We develop a fast implementation for the new method based on coordinate descent. Furthermore, we show how the new methods can be applied to time-to-event data. The new method yields good results in simulation studies concerning sensitivity and specificity of non-zero covariate coefficients, estimation of networ…

Clustering high-dimensional databusiness.industryjel:C41jel:C13Machine learningcomputer.software_genreRegressionhigh-dimensional data gene expression data pathway information penalized regressionConnection (mathematics)Set (abstract data type)Lasso (statistics)CovariateArtificial intelligenceSensitivity (control systems)businessCoordinate descentAlgorithmcomputerMathematics
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Returns to Schooling in Spain. How Reliable Are IV Estimates?

2001

This paper studies the Ordinary Least-Squared (OLS) and Instrumental Variables (IV) estimates of the returns to schooling for male workers in Spain. OLS estimates are often biased due to the endogeneity of schooling, measurement errors or omitted variables. Proper IV estimates correct this bias. The reliability of family background, natural experiments (based on changes in the education system and season of birth) and the availability of a college in the province is checked using Spanish data. The results suggest that background and college availability are valid instruments and that the IV estimates of the returns to schooling are higher than OLS estimates. These results are in line with t…

Male workersjel:J24Returns to schooling Instrumental Variables Spanish schooling systemSeason of birthjel:C20Instrumental variableEconomicsEconometricsjel:C13Endogeneityjel:I21
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On the ambiguous consequences of omitting variables

2015

This paper studies what happens when we move from a short regression to a long regression (or vice versa), when the long regression is shorter than the data-generation process. In the special case where the long regression equals the data-generation process, the least-squares estimators have smaller bias (in fact zero bias) but larger variances in the long regression than in the short regression. But if the long regression is also misspecified, the bias may not be smaller. We provide bias and mean squared error comparisons and study the dependence of the differences on the misspecification parameter.

Statistics::TheoryMean squared errorjel:C52Regression dilutionjel:C51Local regressionjel:C13Regression analysisOmitted-variable biasCross-sectional regressionStatistics::ComputationOmitted variables Misspecification Least-squares estimators Bias Mean squared errorStatistics::Machine LearningStatisticsEconometricsStatistics::MethodologyRegression diagnosticNonlinear regressionMathematics
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Validation procedures in radiological diagnostic models. Neural network and logistic regression

1999

The objective of this paper is to compare the performance of two predictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validatio…

Validation methodsReceiver operating characteristicArtificial neural networkComputer scienceRadiological weaponResamplingSkull neoplasms logistic regression neural networks receiver operating characteristic curve statistics resamplingStatisticsWord error ratejel:C13Logistic regressionCross-validationjel:C14
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Common functional component modelling

2005

Functional data analysis (FDA) has become a popular technique in applied statistics. In particular, this methodology has received considerable attention in recent studies in empirical finance. In this talk we discuss selected topics of functional principal components analysis that are motivated by financial data.

nonparametric risk management generalized hyperbolic distribution functional data analysisjel:G19jel:C13
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Organizational Wellness Modeling

2009

The aim of the present paper is to establish certain mathematical models for organizational wellness as well as to create some wellness optimization problems applicable to any type of organization (including universities) that might be mathematically solved resorting to aspects of operational research of mathematical analysis. The results obtained associated with a mathematical apparatus enable one to perform analyses, comparisons, interpretations, predictions. All of us have, consciously or not, a genuine curiosity in creating and shaping organizational wellness. This concept represents a highly topical issue since professional activity, irrespective of its field, holds a very significant …

organizational wellness; mathematical models; social processes modelling.jel:C51jel:C13jel:I31REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT
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