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On approximation of Markov binomial distributions
, 2009
"... For a Markov chain X = {Xi, i = 1, 2,..., n} with the state space {0, 1}, the random variable S:= ∑n i=1Xi is said to follow a Markov binomial distribution. The exact distribution of S, denoted as LS, is very computationally intensive for large n [see Gabriel (1959) and Bhat and Lal (1988)] and this ..."
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For a Markov chain X = {Xi, i = 1, 2,..., n} with the state space {0, 1}, the random variable S:= ∑n i=1Xi is said to follow a Markov binomial distribution. The exact distribution of S, denoted as LS, is very computationally intensive for large n [see Gabriel (1959) and Bhat and Lal (1988
Testing Poisson Binomial Distributions
"... A Poisson Binomial distribution over n variables is the distribution of the sum of n independent Bernoullis. We provide a sample nearoptimal algorithm for testing whether a distribution P supported on {0,..., n} to which we have sample access is a Poisson Binomial distribution, or far from all Poi ..."
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A Poisson Binomial distribution over n variables is the distribution of the sum of n independent Bernoullis. We provide a sample nearoptimal algorithm for testing whether a distribution P supported on {0,..., n} to which we have sample access is a Poisson Binomial distribution, or far from all
A MARKOVBINOMIAL DISTRIBUTION
"... Let {Xi, i ≥ 1} denote a sequence of {0,1}variables and suppose that the sequence forms a Markov Chain. In the paper we study the number of successes Sn = X1 + X2 + · · · + Xn and we study the number of experiments Y (r) up to the rth success. In the i.i.d. case Sn has a binomial distribution an ..."
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Let {Xi, i ≥ 1} denote a sequence of {0,1}variables and suppose that the sequence forms a Markov Chain. In the paper we study the number of successes Sn = X1 + X2 + · · · + Xn and we study the number of experiments Y (r) up to the rth success. In the i.i.d. case Sn has a binomial distribution
Symmetric generalized binomial distributions
, 2014
"... In two recent articles we have examined a generalization of the binomial distribution associated with a sequence of positive numbers, involving asymmetric expressions of probabilities that break the symmetry winloss. We present in this article another generalization (always associated with a seque ..."
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In two recent articles we have examined a generalization of the binomial distribution associated with a sequence of positive numbers, involving asymmetric expressions of probabilities that break the symmetry winloss. We present in this article another generalization (always associated with a
A Bound on the Binomial Approximation to the Beta Binomial Distribution
"... We use the wfunction and the Stein identity to give a result on the binomial approximation to the betabinomial distribution in terms of the total variation distance between the betabinomial and binomial distributions and its upper bound. ..."
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Cited by 3 (2 self)
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We use the wfunction and the Stein identity to give a result on the binomial approximation to the betabinomial distribution in terms of the total variation distance between the betabinomial and binomial distributions and its upper bound.
A GRAPHICAL ILLUSTRATION OF BINOMIAL DISTRIBUTIONS
"... Binomial distribution, along with normal distribution, plays an important role in school mathematics. However, in all reality, students rely simply on memorization even for its simple properties such as average or variance therefore most students struggle to study binomial distribution and its appli ..."
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Binomial distribution, along with normal distribution, plays an important role in school mathematics. However, in all reality, students rely simply on memorization even for its simple properties such as average or variance therefore most students struggle to study binomial distribution and its
The truncated negative binomial distribution
 Biometrika
, 1955
"... extensively used for the description of data too heterogeneous to be fitted by a Poisson distribution. Observed samples, however, may be truncated, in the sense that the number ..."
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Cited by 4 (0 self)
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extensively used for the description of data too heterogeneous to be fitted by a Poisson distribution. Observed samples, however, may be truncated, in the sense that the number
Poisson Approximation to the Beta Binomial Distribution
"... A result of the Poisson approximation to the beta binomial distribution in terms of the total variation distance and its upper bound is obtained by using the wfunction and the SteinChen identity. ..."
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A result of the Poisson approximation to the beta binomial distribution in terms of the total variation distance and its upper bound is obtained by using the wfunction and the SteinChen identity.
Binomial distribution Basics
, 2009
"... Haldane’s prior Jeffreys’s prior Sample size and choice of prior Poisson distribution ..."
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Haldane’s prior Jeffreys’s prior Sample size and choice of prior Poisson distribution
Results 1  10
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121,772