نتایج جستجو برای: yi

تعداد نتایج: 5209  

2001
SVANTE JANSON

SVANTE JANSON Abstract. Consider a sum ∑N 1 Yi of random variables conditioned on a given value of the sum ∑N 1 Xi of some other variables, where Xi and Yi are dependent but the pairs (Xi, Yi) form an i.i.d. sequence. We consider here the case when each Xi is discrete. We prove, for a triangular array ((Xni, Yni)) of such pairs satisfying certain conditions, both convergence of the distribution...

Journal: :J. Applied Probability 2015
Svante Janson

It is well-known that the central limit theorem holds for partial sums of a stationary sequence (Xi) of m-dependent random variables with finite variance; however, the limit may be degenerate with variance 0 even if Var(Xi) 6= 0. We show that this happens only in the case when Xi − EXi = Yi − Yi−1 for an (m − 1)-dependent stationary sequence (Yi) with finite variance (a result implicit in earli...

2003
H. Wakita M. Henon

Lorenz (1963) has investigated a system of three first-order differential equations, whose solutions tend toward a “strange attractor”. We show that the same properties can be observed in a simple mapping of the plane defined by: .yi+,= yi+ l-a-K;, yi+l = bx,. Numerical experiments are carried out for a= 1.4, b = 0.3, Depending on the initial point (x,, yO), the sequence of points obtained by i...

2017
Anna R. Karlin

We are given a training set S = {(xi, yi), 1 ≤ i ≤ m}, where each xi is an instance in some space X, e.g. a feature vector over Rd, and yi is a binary label (classification). For example, xi could be a set of features of an email message and y could be a label indicating whether it is spam or not. We assume that yi = f(xi) where f : X → {0, 1} is the correct labeling of the message, i.e., the g...

2011
Jianjing Kuang

This study aims to provide a better understanding of the phonetic realization of phonation contrast in register contrast languages and its interaction with vowels and tones by comparing the production of two Yi languages: Southern Yi and Bo. Results show that 1) Electroglottographic contact quotient is the essential mechanism of the phonation contrast in both languages; 2) Phonation mainly infl...

2009

Verbeke et al.[1] proved this equivalence for the mixed effects model, where Σi = ZiDZi + σ wI. This model has the special feature that conditional on the random effects, the observations are independent. The DEX model does not follow this structure. The proof given here is for a general response covariance matrix, Σi , and thus extends their results. Suppose that we have subject-specific inter...

2015
Sui-Lung Su Hsin-Yi Yang Chia-Chao Wu Sen-Yeong Kao Yu-Lung Chiu Jin-Shuen Chen Fung-Chang Sung Ying-Chin Ko Shang-Jyh Hwang Ming-Cheng Wang Yung-Ho Hsu Mei-Yi Wu Hung-Yi Chiu Chin Lin SenYeong Kao Kuo-Cheng Lu Ching-Huang Lai Chien-Te Lee Yu Yang Chih-Wei Yang Yu-Mei Hsueh Yuh-Feng Lin

Sui-Lung Su ([email protected]) Chin Lin ([email protected]) Hsin-Yi Yang ([email protected]) Chia-Chao Wu ([email protected]) Sen-Yeong Kao ([email protected]) Kuo-Cheng Lu ([email protected]) Yu-Lung Chiu ([email protected]) Jin-Shuen Chen ([email protected]) Fung-Chang Sung ([email protected]) Ying-Chin Ko ([email protected]) Chien-Te Lee (c...

2002
Jae Kwang Kim

Consider a finite population of N elements identified by a set of indices U = {1, 2, ..., N}. Associated with each unit i in the population there is a study variable yi and a vector xi of auxiliary variables. Let A denote the set of indices for the elements in a sample selected by a set of probability rules called the sampling mechanism. Let the population quantity of interest be θN = ∑N i=1 yi...

2008
Kristi Kuljus

Let Y1, . . . , Yn be independent but not identically distributed random variables with densities f1, . . . , fn symmetric around zero. Suppose c1,n, . . . , cn,n are given constants such that ∑ i ci,n = 0 and ∑ i c 2 i,n = 1. Denote the rank of Yi −∆ci,n for any ∆ ∈ R by R(Yi −∆ci,n) and let an(i) be a score defined via a score function φ. We study the linear rank statistic Sn(∆) = n ∑ i=1 ci,...

2008

Theorem 1. Assume that β ∈ R and that X is a n × k matrix of rank k < n. Let Y1, . . . , Yn are independent normally distributed random variables with mean vector μ = Xβ. Then, the likelihood ratio test of the hypothesis H0 : Aβ = 0 versus H1 : Aβ 6= 0. where A is a q × k matrix has critical region C = {y;F (y) ≥ F0}. F is given by F (y) = ∑n i=1(yi − ̂̂ μi) −∑ni=1(yi − μ̂i) ∑n i=1(yi − μ̂i) n− k q...

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