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211.
We study how the seat value perceived by consumers attending an event in a theater/stadium depends on the location of their seat relative to the stage/field. We develop a measure of seat value, called the Seat Value Index, and relate it to seat location and consumer characteristics. We implement our analysis on a proprietary data set that a professional baseball franchise in Japan collected from its customers, and provide recommendations. For instance, we find that customers seated in symmetric seats on left and right fields might derive very different valuations from the seats. We also find that the more frequent visitors to the stadium report extreme seat value less often when compared with first‐time visitors. Our findings and insights remain robust to the effects of price and game‐related factors. Thus, our research quantifies the significant influence of seat location on the ex‐post seat value perceived by customers. Utilizing the heterogeneity in seat values at different seat locations, we provide segment‐specific pricing recommendations based on a service‐level objective that would limit the fraction of customers experiencing low seat value to a desired threshold. 相似文献
212.
In the multiple linear regression analysis, the ridge regression estimator and the Liu estimator are often used to address multicollinearity. Besides multicollinearity, outliers are also a problem in the multiple linear regression analysis. We propose new biased estimators based on the least trimmed squares (LTS) ridge estimator and the LTS Liu estimator in the case of the presence of both outliers and multicollinearity. For this purpose, a simulation study is conducted in order to see the difference between the robust ridge estimator and the robust Liu estimator in terms of their effectiveness; the mean square error. In our simulations, the behavior of the new biased estimators is examined for types of outliers: X-space outlier, Y-space outlier, and X-and Y-space outlier. The results for a number of different illustrative cases are presented. This paper also provides the results for the robust ridge regression and robust Liu estimators based on a real-life data set combining the problem of multicollinearity and outliers. 相似文献
213.
M. Revan Özkale 《统计学通讯:模拟与计算》2013,42(5):1143-1186
In this study, the performance of the estimators proposed in the presence of multicollinearity in the linear regression model with heteroscedastic or correlated or both error terms is investigated under the matrix mean square error criterion. Structures of the autocorrelated error terms are given and a Monte Carlo simulation study is conducted to examine the relative efficiency of the estimators against each other. 相似文献
214.
ABSTRACTThis article considers some different parameter estimation methods in logistic regression model. In order to overcome multicollinearity, the almost unbiased ridge-type principal component estimator is proposed. The scalar mean squared error of the proposed estimator is derived and its properties are investigated. Finally, a numerical example and a simulation study are presented to show the performance of the proposed estimator. 相似文献
215.
M. Revan Özkale 《统计学通讯:理论与方法》2013,42(7):1094-1097
216.
In the presence of multicollinearity problem, ordinary least squares (OLS) estimation is inadequate. To circumvent this problem, two well-known estimation procedures often suggested are the unbiased ridge regression (URR) estimator given by Crouse et al. (1995) and the (r, k) class estimator given by Baye and Parker (1984). In this article, we proposed a new class of estimators, namely modified (r, k) class ridge regression (MCRR) which includes the OLS, the URR, the (r, k) class, and the principal components regression (PCR) estimators. It is based on a criterion that combines the ideas underlying the URR and the PCR estimators. The standard properties of this new class estimator have been investigated and a numerical illustration is done. The conditions under which the MCRR estimator is better than the other two estimators have been investigated. 相似文献
217.
This article primarily aims to put forward the linearized restricted ridge regression (LRRR) estimator in linear regression models. Two types of LRRR estimators are investigated under the PRESS criterion and the optimal LRRR estimators and the optimal restricted generalized ridge regression estimator are obtained. We apply the results to the Hald data and finally make a simulation study by using the method of McDonald and Galarneau. 相似文献
218.
AbstractIn this article, when it is suspected that regression coefficients may be restricted to a subspace, we discuss the parameter estimation of regression coefficients in a multiple regression model. Then, in order to improve the preliminary test almost ridge estimator, we study the positive-rule Stein-type almost unbiased ridge estimator based on the positive-rule stein-type shrinkage estimator and almost unbiased ridge estimator. After that, quadratic bias and quadratic risk values of the new estimator are derived and compared with some relative estimators. And we also discuss the option of parameter k. Finally, we perform a real data example and a Monte Carlo study to illustrate theoretical results. 相似文献
219.
Timo Teräsvirta 《统计学通讯:理论与方法》2013,42(14):1595-1601
In the paper homogeneous linear estimators of the parameter vector of the general linear model are compared in terms of their MSE matrices. A necessary and sufficient condition for the difference of two MSE matrices to be positive definite is obtained and its practical existence discussed. The non-negative definiteness of the difference also receives attention, and conditions for this case are discussed. The absence of any conditions of the above type is taken into consideration as well. 相似文献
220.
以2003—2011年我国30个省(自治区、直辖市)的面板数据为样本,运用传统面板回归模型和分位数回归模型探讨了环境规制对区域就业的影响及其变化情况。研究结果表明:在模型中不加入环境规制二次项时,其对区域就业有显著的促进作用,且随着分位数的增加,这种促进作用呈先增后降态势;在模型中加入环境规制二次项时,则环境规制与区域就业存在"U"型非线性关系,即当其超过某一强度时,会对区域就业产生促进作用。 相似文献