A paradox on the spectral representation of stationary random processes
In this note our aim is to show a paradox in the spectral representation of stationary random processes.
stat.OT↗
arXiv subjects
Afshin Parvardeh
Publications and source records attributed to Afshin Parvardeh.
A drainage network with dependence and the Brownian web
We study a system of coalescing random walks on the integer lattice $\mathbb{Z}^{d}$ in which the walk is oriented in the $d$-th direction and follows certain specified rules. We first study the geometry of the paths and show that, almost surely, the paths from a graph consisting of just one tree for dimentions $d=2,3$ and infinitely many disjoint trees for dimensions $d\geq 4$. Also, there is no bi-infinite path in the graph almost surely for $d\geq 2$. Subsequently, we prove that for $d=2$ the diffusive scaling of this system converges in distribution to the Brownian web.
math.PR↗
A ranked-based estimator of the mean past lifetime with its application
The mean past lifetime (MPL) is an important tool in reliability and survival analysis for measuring the average time elapsed since the occurrence of an event, under the condition that the event has occurred before a specific time $t>0$. This article develops a nonparametric estimator for MPL based on observations collected according to ranked set sampling (RSS) design. It is shown that the estimator that we have developed is a strongly uniform consistent. It is also proved that the introduced estimator tends to a Gaussian process under some mild conditions. A Monte Carlo simulation study is employed to evaluate the performance of the proposed estimator with its competitor in simple random sampling (SRS). Our findings show the introduced estimator is more efficient than its counterpart estimator in SRS as long as the quality of ranking is better than random. Finally, an illustrative example is provided to describe the potential application of the developed estimator in assessing the average time between the infection and diagnosis in HIV patients.
stat.ME↗
Kernel Mean Embedding of Probability Measures and its Applications to Functional Data Analysis
This study intends to introduce kernel mean embedding of probability measures over infinite-dimensional separable Hilbert spaces induced by functional response statistical models. The embedded function represents the concentration of probability measures in small open neighborhoods, which identifies a pseudo-likelihood and fosters a rich framework for statistical inference. Utilizing Maximum Mean Discrepancy, we devise new tests in functional response models. The performance of new derived tests is evaluated against competitors in three major problems in functional data analysis including function-on-scalar regression, functional one-way ANOVA, and equality of covariance operators.
math.ST↗
Adaptive two-stage sequential double sampling
In many surveys inexpensive auxiliary variables are available that can help us to make more precise estimation about the main variable. Using auxiliary variable has been extended by regression estimators for rare and cluster populations. In conventional regression estimator it is assumed that the mean of auxiliary variable in the population is known. In many surveys we don't have such wide information about auxiliary variable. In this paper we present a multi-phase variant of two-stage sequential sampling based on an inexpensive auxiliary variable associated with the survey variable in the form of double sampling. The auxiliary variable will be used in both design and estimation stage. The population mean is estimated by a modified regression-type estimator with two different coefficient. Results will be investigated using some simulations following Median and Thompson (2004).
math.ST↗