partial sum process
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Author(s):  
Emad-Eldin A. A. Aly

Objectives: To study the asymptotic theory of the randomly wieghted partial sum process of powers of k-spacings from the uniform distribution. Methods: Earlier results on the distribution of the uniform incremental randomly weighted sums. Methods: Based on theorems on weak and strong approximations of partial sum processes. Results and conculsions: Our main contribution is to prove the weak convergence of weighted sum of powers of uniform spacings.


Extremes ◽  
2012 ◽  
Vol 16 (1) ◽  
pp. 39-54
Author(s):  
Arnold Janssen ◽  
Markus Pauly

Extremes ◽  
2005 ◽  
Vol 8 (1-2) ◽  
pp. 43-56 ◽  
Author(s):  
Arup Bose ◽  
Sreela Gangopadhyay ◽  
Anish Sarkar

2002 ◽  
Vol 18 (1) ◽  
pp. 119-139 ◽  
Author(s):  
Qiying Wang ◽  
Yan-Xia Lin ◽  
Chandra M. Gulati

Let Xt be a linear process defined by Xt = [sum ]k=0∞ ψkεt−k, where {ψk, k ≥ 0} is a sequence of real numbers and {εk, k = 0,±1,±2,...} is a sequence of random variables. Two basic results, on the invariance principle of the partial sum process of the Xt converging to a standard Wiener process on [0,1], are presented in this paper. In the first result, we assume that the innovations εk are independent and identically distributed random variables but do not restrict [sum ]k=0∞ |ψk| < ∞. We note that, for the partial sum process of the Xt converging to a standard Wiener process, the condition [sum ]k=0∞ |ψk| < ∞ or stronger conditions are commonly used in previous research. The second result is for the situation where the innovations εk form a martingale difference sequence. For this result, the commonly used assumption of equal variance of the innovations εk is weakened. We apply these general results to unit root testing. It turns out that the limit distributions of the Dickey–Fuller test statistic and Kwiatkowski, Phillips, Schmidt, and Shin (KPSS) test statistic still hold for the more general models under very weak conditions.


1999 ◽  
Vol 15 (5) ◽  
pp. 704-709 ◽  
Author(s):  
Jonathan H. Wright

It is possible to construct a test of the null of no fractional integration that has nontrivial asymptotic power against a sequence of alternatives specifying that the series is I(d) with d = O(T−1/2), where T is the sample size. In this paper, I show that tests for fractional integration that are based on the partial sum process of the time series have only trivial asymptotic power (i.e., equal to the size) against this sequence of local alternatives. These tests include the rescaled-range test. In this sense, despite its widespread use in empirical work, the rescaled-range test is a poor test for fractional integration.


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