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Expected Numbers at Hitting Times
 J. Graph Theory
, 1991
"... We determine exactly the expected number of hamilton cycles in the random graph obtained by starting with n isolated vertices and adding edges at random until each vertex degree is at least two. This complements recent work of Cooper and Frieze. There are similar results concerning expected numbers ..."
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Cited by 2 (0 self)
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We determine exactly the expected number of hamilton cycles in the random graph obtained by starting with n isolated vertices and adding edges at random until each vertex degree is at least two. This complements recent work of Cooper and Frieze. There are similar results concerning expected numbers
On the Expected Number of kSets
 DISCRETE COMPUT GEOM 1 L:243263 (1994) DISCRETE & COMPUTATIONAL GEOMETRY 9 1994
, 1994
"... Given a set S of n points in R a, a subset X of size d is called a ksimplex if the hyperplane aft(X) has exactly k points on one side. We study Ed(k, n), the expected number of ksimplices when S is a random sample of n points from a probability distribution P on R d. When P is spherically symmetri ..."
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Cited by 7 (0 self)
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Given a set S of n points in R a, a subset X of size d is called a ksimplex if the hyperplane aft(X) has exactly k points on one side. We study Ed(k, n), the expected number of ksimplices when S is a random sample of n points from a probability distribution P on R d. When P is spherically
An algorithm for finding best matches in logarithmic expected time
 ACM Transactions on Mathematical Software
, 1977
"... An algorithm and data structure are presented for searching a file containing N records, each described by k real valued keys, for the m closest matches or nearest neighbors to a given query record. The computation required to organize the file is proportional to kNlogN. The expected number of recor ..."
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Cited by 759 (2 self)
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An algorithm and data structure are presented for searching a file containing N records, each described by k real valued keys, for the m closest matches or nearest neighbors to a given query record. The computation required to organize the file is proportional to kNlogN. The expected number
Expected stock returns and volatility
 Journal of Financial Economics
, 1987
"... This paper examines the relation between stock returns and stock market volatility. We find evidence that the expected market risk premium (the expected return on a stock portfolio minus the Treasury bill yield) is positively related to the predictable volatility of stock returns. There is also evid ..."
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Cited by 674 (9 self)
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This paper examines the relation between stock returns and stock market volatility. We find evidence that the expected market risk premium (the expected return on a stock portfolio minus the Treasury bill yield) is positively related to the predictable volatility of stock returns. There is also
Liquidity Risk and Expected Stock Returns
, 2002
"... This study investigates whether marketwide liquidity is a state variable important for asset pricing. We find that expected stock returns are related crosssectionally to the sensitivities of returns to fluctuations in aggregate liquidity. Our monthly liquidity measure, an average of individualsto ..."
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Cited by 590 (4 self)
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This study investigates whether marketwide liquidity is a state variable important for asset pricing. We find that expected stock returns are related crosssectionally to the sensitivities of returns to fluctuations in aggregate liquidity. Our monthly liquidity measure, an average of individual
The crosssection of expected stock returns
 Journal of Finance
, 1992
"... Your use of the JSTOR archive indicates your acceptance of JSTOR ' s Terms and Conditions of Use, available at ..."
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Cited by 1945 (23 self)
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Your use of the JSTOR archive indicates your acceptance of JSTOR ' s Terms and Conditions of Use, available at
Expected Time Bounds for Selection
, 1975
"... A new selection algorithm is presented which is shown to be very efficient on the average, both theoretically and practically. The number of comparisons used to select the ith smallest of n numbers is n q min(i,ni) q o(n). A lower bound within 9 percent of the above formula is also derived. ..."
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Cited by 466 (4 self)
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A new selection algorithm is presented which is shown to be very efficient on the average, both theoretically and practically. The number of comparisons used to select the ith smallest of n numbers is n q min(i,ni) q o(n). A lower bound within 9 percent of the above formula is also derived.
Fitting a mixture model by expectation maximization to discover motifs in biopolymers
 Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology
, 1994
"... ABSTRACT: The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expectation maximization to fit a twocomponent finite mixture model to the set of sequences. Multiple motifs are found by fitting a twocomponent finite ..."
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Cited by 941 (5 self)
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ABSTRACT: The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expectation maximization to fit a twocomponent finite mixture model to the set of sequences. Multiple motifs are found by fitting a two
The expected number of runs in a word
 AUSTRALASIAN JOURNAL OF COMBINATORICS VOLUME 42 (2008), PAGES 45–54
, 2008
"... A word is a sequence of symbols taken from a (usually finite) alphabet. A run of period p in a word x is a factor x[m..n] such that n − m ≥ p and x[i] =x[i+p] for all i satisfying m ≤ i<i+p ≤ n, and such that this does not hold if m is replaced by a smaller integer or n by a larger one. The numbe ..."
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Cited by 4 (1 self)
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. The number of runs in words has been a subject of interest in recent years, particularly because of connections with data compression. In this paper we investigate the expected number of runs per unit length in words of given alphabet size, and compare our results with DNA, amino acid and other sequences.
Results 1  10
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