Title
Kernel Estimation for the Mode and Quantiles of Time Series: Advanced Text in Statistics,Used
Delivery time: 8-12 business days (International)
In this book, we are interested in the area of nonparametric prediction of time series. Therefore, the relationship between a current observation and past observations is considered, where the conditional density function plays an important role. Two aspects of the conditional probability density function, the mode and the quantiles are studied. Firstly, in the case of the mode, we state some sufficient conditions under which the joint kernel estimator of the conditional mode taken jointly at a finite number of distinct points is asymptotically normally distributed. Secondly, a new multivariate estimator for a multivariate conditional quantile is proposed, based on the reweighted NadarayaWatson estimator for the conditional cumulative distribution function. The efficiency of the proposed estimator is tested by giving two applications. The book also, involves a review which covers in sufficient details the up to date literature on kernel estimation for conditional mode and quantiles.
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We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
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This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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