Jackknife Parameter Estimator Research Papers (original) (raw)

• Top Papers
• Most Cited Papers
• Most Downloaded Papers
• Newest Papers
• People

In order to estimate model parameters in multiple regression models, resampling methods of bootstrap and jackknife are used. Resampling methods are used as an alternative readjustment method to the least squares method (OLS) especially... more

In order to estimate model parameters in multiple regression models, resampling methods of bootstrap and jackknife are used. Resampling methods are used as an alternative readjustment method to the least squares method (OLS) especially when assumptions belonging to error term in regression analysis are not met. Data used in the study are taken from 25 advertisements in Sahibinden.com website and the price of beetle car brand is accepted as dependent variable for multiple linear regression models. It is aimed that price variable taken is tried to be explained with the help of variables of fuel, case type, salesman, sunroof, wind shield, upholstery, age and engine size. When we examined the variables, it is seen that categorical variables are in question and dummy variable must be used. Firstly, model parameters of this obtained data are estimated using OLS and significances of parameters are tested, then, model parameters, significances of estimated parameters, coefficient of determination, and standard error of the model and % 90 confidence intervals are estimated using one of the resampling methods, bootstrap and jackknife method and results belonging to these three methods are compared. Also, generalization condition, which is to the population, of parameter estimation results belonging to explanatory variables used in this study are reviewed with the help of jackknife resampling method ve It has been seen that the salesman and upholstery independent variables have a considerable effect at a significance level of .10 on the dependent variable of price dependence of decision making (p < .10) and Jackknife have confirmed these generalization.

• • by
  • •
  • Resampling Methods, Bootstrap (Statistics), Multiple Linear Regression, Jackknife Parameter Estimator

Resampling methods offers effective estimates of parameters and its asymptotic distribution. In this study, it is recommended to use the bootstrap method as an alternative to the classical and knife (one exclusion procedure) test... more

Resampling methods offers effective estimates of parameters and its asymptotic distribution. In this study, it is recommended to use the bootstrap method as an alternative to the classical and knife (one exclusion procedure) test statistics in evaluating the significance of the Pearson correlation coefficient by applying the bootstrap method to the simple linear regression model. This procedure provides an effective alternative to test the significance of the Pearson correlation coefficient. In the application, the model parameters, standard errors, Pearson coefficients of correlation, bias and % 95 confidence intervals belonging to bootstrap and jackknife methods in estimated with the help of a real data and the obtained results are interpreted. As a result, the test statistic obtained by the bootstrap method is proposed as an alternative to the classical and jackknife test statistics.

• • by Tolga ZAMAN
  • •
  • Bootstrap (Statistics), Bootstrapping method, Bootstrap, Jackknife