[PDF] Top 20 Quantile Regression with Telematics Information to
Has 10000 "Quantile Regression with Telematics Information to" found on our website. Below are the top 20 most common "Quantile Regression with Telematics Information to".
Quantile Regression with Telematics Information to
... find that, at different percentile levels, the distance driven at speeds above the posted limit depends1. 14.[r] ... See full document
10
Combined Estimation for Quantile Regression
... combining information from two quantiles (CQAR1) can be ...the quantile function to be minimized. The aggregation across quantile levels improves the efficiency of the estimation, thus benefits the ... See full document
103
Quantile Regression for Repeated Responses Measured with Error.
... Many problems in biostatistics involve response variables that are either unobservable or difficult to measure. Muscular strength in animals and humans quantified through the grip strength is an example of such a variable. ... See full document
107
Innovation and market value: A quantile regression analysis
... 2006). Information on the factor loadings is shown in Table ...of information on a firm’s innovative activity can be summarized into one variable (this will be especially useful in the following ... See full document
10
Demand for International Reserves: A Quantile Regression Approach
... Earlier studies that examine the demand for international reserves during the 1960’s also found significant differences between the demand functions of more open and less open nations (Kelly, 1970) and developed and ... See full document
21
A quantile regression approach to bank efficiency measurement
... differences across different levels of development, we combine information from the International Monetary Fund IMF and the European Bank for Reconstruction and Development EBRD, and we [r] ... See full document
21
Nonparametric circular quantile regression
... external information, or data could be confined to a small arc of the circle (reproducing an euclidean-like scenario), but more generally (as in our example) we could choose the origin according to a minimum width ... See full document
16
Bayesian Quantile Regression in Biostatistical Applications.
... the quantile functions of birth weight and gestational age to ozone exposure and multiple predictors, including parental age, race, and education ...Bayesian quantile model that collectively estimates the ... See full document
127
Which quantile is the most informative? Maximum likelihood, maximum entropy and quantile regression
... τ-th quantile, and the mode of the ...important information from the data a good summary statistic would be to choose one order statistics accordingly the most likely ...likely quantile in a ... See full document
41
Quantile regression for overdispersed count data: a hierarchical method
... Poisson regression is commonly applied to overdispersed count data, and focused on modelling the conditional mean of the ...mean regression models may be sensitive to response outliers and provide no ... See full document
19
High quantile regression for extreme events
... provide information about extreme heavy snowfalls that may cause ...The quantile regression method will be able to estimate the high conditional ... See full document
20
Poverty and Intelligence: Evidence Using Quantile Regression
... The strength of the empirical analysis of Lynn and Vanhanen (2006) has never really been studied. For more recently, Mani et al. (2013) showed that poverty also affects cognitive Capacities . This result is in line with ... See full document
10
Efficient Estimation of an Additive Quantile Regression Model
... Motivated by the additive conditional quantile set-up (5.4), our aim is to compare our oracle efficient estimates of the additive quantiles and the corresponding estimates from the semi- parametric approach. It ... See full document
36
Bayesian CV@R/super quantile regression
... In this paper we provide a Bayesian interpretation of the conditional value at risk, CV@R, or super-quantile regression recently developed by Rockafellar, Royset and Miranda (2014). Computations are based ... See full document
20
Weighted Type of Quantile Regression and its Application
... composite quantile regression (CQR) estimation approach and study its application in nonlinear models such as exponential models and ARCH type of ...from quantile regression and achieve nearly ... See full document
5
Asymptotics for panel quantile regression models with individual effects
... the quantile structural function defined in Imbens and Newey (2009) of a nonseparable panel model with discrete explanatory ...the quantile structural function when T is fixed and the asymptotic behavior of ... See full document
43
Are there asymmetries in the effects of training on the conditional male wage distribution?
... linear regression framework (see inter alia references in Ashenfelter and Lalonde, 1996; and Arulampalam and Booth, ...conditional quantile regression model was first introduced by Koenker and ... See full document
35
Statistical Methods Useful in Clinical Simulation and Medical Education Scholarship
... between maternal tobacco smoking during pregnancy and the outcome of infant mortality. A DAG illustrating this relationship would most likely show that maternal smoking leads to low birth weight which in turn influences ... See full document
9
Predicting word reading ability:a quantile regression study
... used quantile regression analysis: this technique enabled us to examine how each predictor was related to word reading individually at different quantiles, and how predictors were uniquely related to word ... See full document
31
Double Penalized Quantile Regression in Partially Linear Models
... tant ones is usually relatively small. Therefore, selection of important explanatory variables is often one of the most important goals in the real data analysis. In this paper, we are interested in automatic selection, ... See full document
7
Related subjects