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OLS regressions with the dependent variable ROA:

Variable Selection for Covariate Dependent Dirichlet Process Mixtures of Regressions

Variable Selection for Covariate Dependent Dirichlet Process Mixtures of Regressions

... perform variable selection and recently they have been employed in non-parametric settings in context of DPM of ...is dependent on the particular pattern in the covariates when fitting a ...of ...

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Integrated Modified OLS Estimation and Fixed-b Inference for Cointegrating Regressions

Integrated Modified OLS Estimation and Fixed-b Inference for Cointegrating Regressions

... data dependent bandwidth rule of Andrews ...the OLS, FM and DOLS statistics are carried out using N (0, 1) critical values in all cases and also the rejections for IM(O) and IM(D) are carried out using N ...

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The Asymptotic Validity of "Standard" Fully Modified OLS Estimation and Inference in Cointegrating Polynomial Regressions

The Asymptotic Validity of "Standard" Fully Modified OLS Estimation and Inference in Cointegrating Polynomial Regressions

... the dependent variable not only of FM-CPR, but also by the first-step modification of FM-STD, if the first powers of the integrated regressors are all included in the ...

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Integrated modified OLS estimation for cointegrating polynomial regressions - with an application to the environmental Kuznets curve for CO2 emissions

Integrated modified OLS estimation for cointegrating polynomial regressions - with an application to the environmental Kuznets curve for CO2 emissions

... The theoretical analysis is complemented by a small simulation study to assess the finite sample performance of the estimators in terms of bias and root mean squared error (RMSE); as well as the test performance in terms ...

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Illustrating Instrumental Variable Regressions Using the Career Adaptability – Job Satisfaction Relationship

Illustrating Instrumental Variable Regressions Using the Career Adaptability – Job Satisfaction Relationship

... traditional OLS regression estimates and how 2SLS regression returns consistent estimates of an endogenous predictor on its outcome, provided that IVs—exogenous and relevant sources of variance—are ...the ...

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Regression Split by Levels of the Dependent Variable

Regression Split by Levels of the Dependent Variable

... on OLS coefficients. OLS yields the best aggregate of predictors to fit data – and it is perfect for prediction – but it was not designed to obtain meaningful coefficients for individual predictors in ...

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GLM with a Gamma-distributed Dependent Variable

GLM with a Gamma-distributed Dependent Variable

... However, I did find out something really important, something which is mentioned in Myers, Mont- gomery, and Vining at several points, but I did not appreciate it until now. The GLM really is different than OLS, ...

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Predictive Regressions

Predictive Regressions

... not dependent on the c 0 i ...instrumental variable approach has originated in the earlier work of Phillips and Magdalinos (2009) who focused on a multivariate cointegrated system closely related to (5)-(6) ...

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Bridging logistic and OLS regression

Bridging logistic and OLS regression

... 2. Estimating Marginal Effects An alternative approach to relying on OLS is to derive the from the logistic regression results the marginal effects of changes in the independent variables on the dependent ...

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Bridging logistic and OLS regression

Bridging logistic and OLS regression

... interpretation as OLS coefficients do. In particular, in the case of OLS the dependent variable is the probability of the event itself (equation 1). p =  0 +  i  i (1) In equation 1, p is ...

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Unconditional Quantile Regressions

Unconditional Quantile Regressions

... The dependent variable is the real log hourly wage for all wage and salary workers, and the explanatory variables including human capital variables and demographic ...

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Regressions Regularized by Correlations

Regressions Regularized by Correlations

... GfK North America Minneapolis, MN The regularization of multiple regression by proportionality to correlations of predictors with dependent variable is applied to the least squares objective and normal ...

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Aid and Growth Regressions

Aid and Growth Regressions

... the regressions using differences, this has been addressed by time-series ...the dependent variable as well as the explanatory variables are included in the regression, have proven to be quite ...

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Predictions in Quantile Regressions

Predictions in Quantile Regressions

... 4. OLS and Quantile Regression Estimates Table 2 presents the OLS and the median regression ...regional variable is negative, reflecting the lag of southern regions; the school track yield positive ...

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Robust Sign-Based and Hodges-Lehmann Estimators in Linear Median Regressions with Heterogenous Serially Dependent Errors

Robust Sign-Based and Hodges-Lehmann Estimators in Linear Median Regressions with Heterogenous Serially Dependent Errors

... pendent variable and a vector of explanatory variables under weak distributional ...Quantile regressions [Koenker and Bassett (1978), Koenker (2005)] can be viewed as extensions of median ...

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An integrated modified OLS RESET test for cointegrating regressions

An integrated modified OLS RESET test for cointegrating regressions

... As is well-known, standard asymptotic theory does not capture the impact of kernel and band- width choices, required for long run variance estimation, on the sampling distributions of estimators and test statistics based ...

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“Linear” fully modified OLS estimation of cointegrating polynomial regressions

“Linear” fully modified OLS estimation of cointegrating polynomial regressions

... cointegrating regressions are routinely ...Modified OLS estimator surprisingly to the same limiting distribution as obtained for the version of the Fully Modified OLS estimator adapted to the ...

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A Note on OLS Multivariate Regressions with Suggestions for Additions to Routine Computer Programmes

A Note on OLS Multivariate Regressions with Suggestions for Additions to Routine Computer Programmes

... In simple regression (i.e... one indvar, say X1) the obvious course would be to reorder the residuals according.. to the magnitude of X1 and then compute DW or tau; if Y or X1 are relate[r] ...

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OLS Examples. OLS Regression

OLS Examples. OLS Regression

... – The slope is highly significant and positive at the 0.0 level indicating that the market rate of return (excess returns) have a positive effect on the returns for the cyclical consum[r] ...

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The revisited knockoffs method for variable selection in $L_1$-penalised regressions.

The revisited knockoffs method for variable selection in $L_1$-penalised regressions.

... Moreover, using Lasso induces the critical choice of the penalty parameter which con- trols the number of selected covariables. This choice is major because two close values of the penalty parameter can often lead to ...

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