A Clipped Gaussian Geo-Classification model for poverty mapping [0.03%]
用于贫困地图匹配的A Clipped Gaussian Geo-Classification模型
Richard Puurbalanta
Richard Puurbalanta
The importance of discrete spatial models cannot be overemphasized, especially when measuring living standards. The battery of measurements is generally categorical with nearer geo-referenced observations featuring stronger dependencies. Th...
Wavelet threshold based on Stein's unbiased risk estimators of restricted location parameter in multivariate normal [0.03%]
基于Stein无偏风险估计的多元正态分布限制下位置参数的阈值小波方法研究
H Karamikabir,M Afshari,F Lak
H Karamikabir
In this paper, the problem of estimating the mean vector under non-negative constraints on location vector of the multivariate normal distribution is investigated. The value of the wavelet threshold based on Stein's unbiased risk estimators...
Jing Zhang,Yanyan Liu
Jing Zhang
For ultrahigh-dimensional data, independent feature screening has been demonstrated both theoretically and empirically to be an effective dimension reduction method with low computational demanding. Motivated by the Buckley-James method to ...
Lahiru Wickramasinghe,Alexandre Leblanc,Saman Muthukumarana
Lahiru Wickramasinghe
We introduce an approach to model the batting outcomes of baseball batters based on the weighted likelihood approach and make use of our methodology to estimate commonly used baseball batting metrics. The weighted likelihood allows the shar...
Estimation of common location parameter of several heterogeneous exponential populations based on generalized order statistics [0.03%]
基于广义订单统计的若干异质指数总体公共位置参数的估计
Qazi J Azhad,Mohd Arshad,Amit Kumar Misra
Qazi J Azhad
In this article, several independent populations following exponential distribution with common location parameter and unknown and unequal scale parameters are considered. From these populations, several independent samples of generalized o...
Opeoluwa F Oyedele
Opeoluwa F Oyedele
At the core of multivariate statistics is the investigation of relationships between different sets of variables. More precisely, the inter-variable relationships and the causal relationships. The latter is a regression problem, where one s...
Quantifying the similarity of 2D images using edge pixels: an application to the forensic comparison of footwear impressions [0.03%]
基于边缘像素的二维图像相似性量化及在鞋印同一认定中的应用研究
Soyoung Park,Alicia Carriquiry
Soyoung Park
We propose a novel method to quantify the similarity between an impression (Q) from an unknown source and a test impression (K) from a known source. Using the property of geometrical congruence in the impressions, the degree of corresponden...
Inference on a progressive type I interval-censored truncated normal distribution [0.03%]
渐近失效时间在截断正态分布下的推断问题
Chandrakant Lodhi,Yogesh Mani Tripathi
Chandrakant Lodhi
In this paper, we consider the problem of making statistical inference for a truncated normal distribution under progressive type I interval censoring. We obtain maximum likelihood estimators of unknown parameters using the expectation-maxi...
Physically constrained spatiotemporal modeling: generating clear-sky constructions of land surface temperature from sparse, remotely sensed satellite data [0.03%]
基于物理的时空模型构建：从稀疏遥感卫星数据中生成地表晴空温度估算
Gavin Q Collins,Matthew J Heaton,Leiqiu Hu
Gavin Q Collins
Satellite remote-sensing is used to collect important atmospheric and geophysical data at various spatial resolutions, providing insight into spatiotemporal surface and climate variability globally. These observations are often plagued with...
An MCMC computational approach for a continuous time state-dependent regime switching diffusion process [0.03%]
一种关于连续时间状态转换扩散过程的MCMC算法研究
El Houcine Hibbah,Hamid El Maroufy,Christiane Fuchs et al.
El Houcine Hibbah et al.
State-dependent regime switching diffusion processes or hybrid switching diffusion (HSD) processes are hard to simulate with classical methods which leads us to adopt a Markov chain Monte Carlo (MCMC) Bayesian approach very convenient to es...