We propose a new family of error distributions for model-based quantile regression, which is constructed through a structured mixture of normal distributions. The construction enables fixing specific percentiles of the distribution while, at the same time, allowing for varying mode, skewness and tail behavior. It thus overcomes the severe limitation of the asymmetric Laplace distribution – the ...

A discrete-continuous choice model of time allocation to two types of discretionary activities is formulated based on the concept of random utility maximization. The model development takes into account the discreteness inherent in daily activity engagement and time allocation (i.e., one type of activity may not be engaged, therefore no time may be allocated to it at all, during a day). Without...

We document some recent changes in the market for loan sales. We use a Tobit model to characterize the determinants of loan sales and purchases by banks, relating quantities bought and sold to bank size, capital, risk, and fbnding mode. The results, though not definitive, broadly confirm the Pennacchi model of sales. Other data cast doubt on the importance of mergers and acquisitions for this m...

Absenteeism research has often been criticized for using inappropriate analysis. Characteristics of absence data, notably that it is usually truncated and skewed, violate assumptions of OLS regression; however, OLS and correlation analysis remain the dominant models of absenteeism research. This piece compares eight models that may be appropriate for analyzing absence data. Specifically, this p...

Concerns about the safe use of clinical ultrasound (US) at diagnostic pressure levels (below a mechanical index, or MI, = 1.9) have stimulated considerable research in US risk assessment. The objective of the present study was to develop probability-based risk thresholds for US safety studies, to present statistical methods for estimating the thresholds and their standard errors and to compare ...

Methods Data from 2 separate non-small cell lung cancer clinical trials (TOPICAL and SOCCAR) are used to develop and validate the BB model. Comparisons with Linear, TOBIT, Quantile, Quadratic and CLAD models were carried out. The mean prediction error, R, proportion predicted outside the valid range, clinical interpretation of coefficients, model fit and estimation of Quality Adjusted Life Year...

Abstract We propose a variational inference-based framework for training Gaussian process regression model subject to censored observational data. Data censoring is typical problem encountered during the data gathering procedure and requires specialized techniques perform inference since resulting probabilistic models are typically analytically intractable. In this article we exploit sparse ind...

Based on a large panel dataset of small commercial banks in the United States, this paper employs dynamic Tobit model to analyse role uncertainty forecasting charge-off rates loans for credit card (CC) and residential real estate (RRE). When compared other standard predictors, such as house prices unemployment rates, we find that effect changes is more pronounced. Furthermore, it evident includ...