Results 281 to 290 of about 12,687,491 (330)

Modeling Over-Dispersed Microbiome Data

2018
However, count data is not purely relative—the count pair (1, 2) carries different information than counts of (1000, 2000) even though the relative amounts of the two components are the same.
Yinglin Xia, Jun Sun, Ding-Geng Chen
openaire   +1 more source

Modeling over-dispersed datasets using generalized geometric distributions

Journal of Statistical Computation and Simulation, 2019
Through this article we propose a class of over-dispersed distributions namely ‘the generalized geometric distribution (GGD)’ as an extension of the well-known ‘geometric distribution’.
C. Satheesh Kumar, S. Harisankar
openaire   +1 more source

Neural Network Embedding of the Over-Dispersed Poisson Reserving Model

SSRN Electronic Journal, 2018
The main idea of this paper is to embed a classical actuarial regression model into a neural network architecture. This nesting allows us to learn model structure beyond the classical actuarial regression model if we use as starting point of the neural network calibration exactly the classical actuarial model.
Andrea Gabrielli, Ronald Richman, Mario V. Wüthrich   +2 more
openaire   +1 more source

Generation of Over-Dispersed and Under-Dispersed Binomial Variates

Journal of Computational and Graphical Statistics, 1995
Abstract This article proposes an algorithm for generating over-dispersed and under-dispersed binomial variates with specified mean and variance. The over-dispersed/under-dispersed distributions are derived from correlated binary variables with an underlying continuous multivariate distribution.
Hongshik Ahn, James J. Chen
openaire   +1 more source

Over‐dispersed count data in crop and agronomy research

Journal of Agronomy and Crop Science, 2019
AbstractWhile evaluating plant response to biotic or abiotic stress and genotype–environment interactions and searching causes of yield gap, very often are observed data with non‐normal distributions. One of the commonly encountered types of variables with a non‐normal distribution is count data. Count data are defined as the type of observations which
Michał Kosma, Marcin Studnicki, Justyna Wójcik‐Seliga, Beata Michalska‐Klimczak, Zdzisław Wyszyński, Elżbieta Wójcik‐Gront   +5 more
openaire   +1 more source

Statistical process control of over-dispersed multivariate count data

2010 IEEE 17Th International Conference on Industrial Engineering and Engineering Management, 2010
Statistical process control of multi-attribute data has received much attention. However, little work has been done on over-dispersed multivariate count data with either positive or negative correlations. In this article, we focus on designing a new control scheme for such kind of data.
Yan-ting Li, Li-feng Xi
openaire   +1 more source

Over-Dispersion, Credibility Adjustments, Mixed Models, and Regularization

2019
Data sets exhibiting a hierarchical or nested structure, or including longitudinal or spatial elements often arise in insurance studies. This generally results in correlation among the responses within the same group, casting doubts about the outputs of analyses assuming mutual independence.
Michel Denuit, Donatien Hainaut, Julien Trufin   +2 more
openaire   +1 more source

Filterbank transceivers optimizing information rate in block transmissions over dispersive channels

IEEE Transactions on Information Theory, 1999
Summary: Optimal finite impulse response (FIR) transmit and receive filterbanks are derived for block-based data transmissions over frequency-selective additive Gaussian noise (AGN) channels by maximizing mutual information subject to a fixed transmit-power constraint. Both FIR and pole-zero channels are considered.
A. SCAGLIONE, BARBAROSSA, Sergio, G. B. GIANNAKIS   +2 more
openaire   +2 more sources

Hydroconversion of Thiophene Derivatives over Dispersed Ni–Mo Sulfide Catalysts

Petroleum Chemistry, 2018
The activity of unsupported Ni–Mo sulfide catalysts is studied in the hydroconversion of benzothiophene and dibenzothiophenes in the temperature range of 340–380°С and at an increased H2 pressure and in the СО/H2О system. The structure of dispersed catalysts formed by the in situ high-temperature decomposition of oil-soluble precursors (molybdenum ...
A. V. Vutolkina, D. F. Makhmutov, A. V. Zanina, A. L. Maximov, D. S. Kopitsin, A. P. Glotov, S. V. Egazar’yants, E. A. Karakhanov   +7 more
openaire   +1 more source

Superoscillating Signal Transmission over Dispersive Media

2023 23rd International Conference on Transparent Optical Networks (ICTON), 2023
Y. Ben-Ezra, B. I. Lembrikov
openaire   +1 more source