Likelihood ratio-type tests in weighted composite quantile regression of DTARCH models
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DOI: 10.1007/s11425-016-9321-x
Abstract: The double-threshold autoregressive conditional heteroscedastic (DTARCH) model is a useful tool to measure and forecast the mean and volatility of an asset return in a financial time series. The DTARCH model can handle situations wherein… read more here.
Keywords: weighted composite; quantile regression; likelihood ratio; dtarch ... See more keywords
Variable selection and weighted composite quantile estimation of regression parameters with left-truncated data
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DOI: 10.1080/03610926.2017.1376089
Abstract: ABSTRACT In this paper, we consider the weighted composite quantile regression for linear model with left-truncated data. The adaptive penalized procedure for variable selection is proposed. The asymptotic normality and oracle property of the resulting… read more here.
Keywords: weighted composite; left truncated; regression; composite quantile ... See more keywords
Empirical likelihood weighted composite quantile regression with partially missing covariates
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DOI: 10.1080/10485252.2016.1272692
Abstract: ABSTRACT This paper develops a novel weighted composite quantile regression (CQR) method for estimation of a linear model when some covariates are missing at random and the probability for missingness mechanism can be modelled parametrically.… read more here.
Keywords: weighted composite; quantile regression; regression; probability ... See more keywords