Skip to search formSkip to main content>Semantic Scholar Semantic Scholar's Logo

Search

You are currently offline. Some features of the site may not work correctly.

Semantic Scholar uses AI to extract papers important to this topic.

Highly Cited

2008

Highly Cited

2008

We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting… Expand

Highly Cited

2007

Highly Cited

2007

Abstract Eigenvectors, and the related centrality measure Bonacich's c(β), have advantages over graph-theoretic measures like… Expand

Review

2003

Review

2003

We review the concept of intra-class correlation in random-effects models for binary outcomes as estimated by Stata's xtprobit… Expand

Highly Cited

2002

Highly Cited

2002

The problem of choosing the correct number of clusters is as old as cluster analysis itself. A number of authors have suggested… Expand

Highly Cited

1995

Highly Cited

1995

From the Publisher:
Artificial "neural networks" are now widely used as flexible models for regression classification… Expand

Highly Cited

1993

Highly Cited

1993

Marginal models for multivariate binary data permit separate modelling of the relationship of the response with explanatory… Expand

Highly Cited

1993

Highly Cited

1993

A new class of convolutional codes called turbo-codes, whose performances in terms of bit error rate (BER) are close to the… Expand

Highly Cited

1993

Highly Cited

1993

Highly Cited

1993

Highly Cited

1993

A circuit implementation of the chaotic Lorenz system is described. The chaotic behavior of the circuit closely matches the… Expand

Review

1970

Review

1970

Binary response variables special logistical analyses some complications some related approaches more complex responses… Expand