An Investigation of Quantile Function Estimators Relative to Quantile Confidence Interval Coverage

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Kernel Quantile Estimators

SUMMARY The estimation of population quantiles is of great interest when one is not prepared to assume a parametric form for the u.nderlying distribution. In addition, quantiles often arise as the natural thing to estimate when the underlying distribution is skewed. The sample quantile is a popular nonparametric estimator of the corresponding population quantile. Being a function of at most two...

متن کامل

New Bandwidth Selection for Kernel Quantile Estimators

We propose a cross-validation method suitable for smoothing of kernel quantile estimators. In particular, our proposed method selects the bandwidth parameter, which is known to play a crucial role in kernel smoothing, based on unbiased estimation of a mean integrated squared error curve of which the minimising value determines an optimal bandwidth. This method is shown to lead to asymptotically...

متن کامل

Probabilistic Error Bounds for Simulation Quantile Estimators

Quantile estimation has become increasingly important, particularly in the financial industry, where value at risk (VaR) has emerged as a standard measurement tool for controlling portfolio risk. In this paper, we analyze the probability that a simulation-based quantile estimator fails to lie in a prespecified neighborhood of the true quantile. First, we show that this error probability converg...

متن کامل

Conditioning your quantile function

Random sampling via a quantile function Q(u) is a popular technique, but two very common sources of numerical instability are often overlooked: (i) quantile functions tend to be ill-conditioned when u → 1 and (ii) feeding them uniformly spaced u can make them ill-conditioned as u → 0. These flaws undermine the tails of Q(u)’s distribution, and both flaws are present in the polar method for norm...

متن کامل

Confidence Corridors for Multivariate Generalized Quantile Regression∗

We focus on the construction of confidence corridors for multivariate nonparametric generalized quantile regression functions. This construction is based on asymptotic results for the maximal deviation between a suitable nonparametric estimator and the true function of interest which follow after a series of approximation steps including a Bahadur representation, a new strong approximation theo...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Communications in Statistics - Theory and Methods

سال: 2014

ISSN: 0361-0926,1532-415X

DOI: 10.1080/03610926.2013.775304