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Extension of the Wald statistic to models with dependent observations
Metrika, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Morales, D. +3 more
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Generalized Cochran–Wald statistics in combining of experiments
Journal of Statistical Planning and Inference, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hartung, Joachim +2 more
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Wald statistic for iiomogeneity of multiple parameters
Communications in Statistics - Theory and Methods, 1999The paper proposes Wald statistic for testing homogeneity of parameters of k populations and gives the asymptotic expansion of the distribution function under a null hypothesis and of power function of it under contiguous alternatives. It shows that Wald statistic is the same as Nagao's statistic (1973) for testing homogeneity of covariance matrices of
Takesi Hayakawa, Masataka Doi
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In this paper a robust version of the classical Wald test statistics for linear hypothesis in the logistic regression model is introduced and its properties are explored.
Ayanendranath Basu +2 more
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Wald statistic for model order selection in superposition models
IEEE Transactions on Signal Processing, 2002A consistent model selection algorithm is presented for superimposed signal models. The proposed method is motivated by the Wald statistic and reduces the computational complexity of procedures based on the minimum description length (MDL) principle. The procedure is suggested when a noncyclostationary signal model or short data length prevents use of ...
Ashutosh Sabharwal, Lee C. Potter
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Wald-based spatial scan statistics for cluster detection
Computational Statistics & Data Analysis, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ying Liu, Yawen Liu, Tonglin Zhang
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‘Wald's Lemma' for sums of order statistics of i.i.d. random variables
Advances in Applied Probability, 1991Let X1, X2, · ··, Xn be positive i.i.d. random variables with known distribution function having a finite mean. For a given s ≥0 we define Nn = N(n, s) to be the largest number k such that the sum of the smallest k Xs does not exceed s, and Mn = M(n, s) to be the largest number k such that the sum of the largest k X's does not exceed s.
Bruss, F Thomas, Robertson, James B
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Pre-checking for non-monotonicity of the Wald statistic
Journal of Statistical Computation and Simulation, 2005The non-monotonic behaviour of the Wald test in some finite-sample applications leads to low power when the null hypothesis needs rejection most. This article proposes a simple check for discerning if the Wald statistic for testing significance of regression coefficients is non-monotonic in the neighbourhood of the parameter space from which the sample
Kim-Leng Goh, Maxwell King
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Obtaining any Wald statistic you want
Economics Letters, 1986Abstract While the Wald test can be used to test a non-linear hypothesis in a linear or non-linear regression model it is known that a particular hypothesis can be written in many ways when non-linear forms are permitted. This paper illustrates that it is possible to obtain virtually any value of the Wald statistic at different significance levels ...
Francine Lafontaine, Kenneth J. White
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