Estimating Covid-19 deaths by using binomial model

2021 ◽  
Author(s):  
Evren Hincal ◽  
Bilgen Kaymakamzade ◽  
Fatma Nese Suren ◽  
Nezihal Gokbulut
Keyword(s):  
Binomial Model

Robust inference in the multilevel zero-inflated negative binomial model

2019 ◽  
Vol 47 (2) ◽  
pp. 287-305 ◽  
Author(s):  
Eghbal Zandkarimi ◽  
Abbas Moghimbeigi ◽  
Hossein Mahjub ◽  
Reza Majdzadeh
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Model ◽  
Robust Inference ◽  
Binomial Model

Panchromatic colorings of random hypergraphs

2021 ◽  
Vol 31 (1) ◽  
pp. 19-41
Author(s):  
D. A. Kravtsov ◽  
N. E. Krokhmal ◽  
D. A. Shabanov
Keyword(s):  
Binomial Model ◽  
Threshold Probability ◽  
The Difference ◽  
Random Hypergraphs

Abstract We study the threshold probability for the existence of a panchromatic coloring with r colors for a random k-homogeneous hypergraph in the binomial model H(n, k, p), that is, a coloring such that each edge of the hypergraph contains the vertices of all r colors. It is shown that this threshold probability for fixed r < k and increasing n corresponds to the sparse case, i. e. the case p = c n / ( n k ) $p = cn/{n \choose k}$ for positive fixed c. Estimates of the form c 1(r, k) < c < c 2(r, k) for the parameter c are found such that the difference c 2(r, k) − c 1(r, k) converges exponentially fast to zero if r is fixed and k tends to infinity.

scholarly journals Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Setting-specific Transmission Rates: A Systematic Review and Meta-analysis

2021 ◽  
Author(s):  
Hayley A Thompson ◽  
Andria Mousa ◽  
Amy Dighe ◽  
Han Fu ◽  
Alberto Arnedo-Pena ◽  
...  
Keyword(s):  
Systematic Review ◽  
Severe Acute Respiratory Syndrome ◽  
Negative Binomial ◽  
Meta Analysis ◽  
Contact Tracing ◽  
Binomial Model ◽  
Transmission Potential ◽  
Transmission Rates ◽  
Symptom Status ◽  
Index Cases

Abstract Background Understanding the drivers of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is crucial for control policies, but evidence of transmission rates in different settings remains limited. Methods We conducted a systematic review to estimate secondary attack rates (SARs) and observed reproduction numbers (Robs) in different settings exploring differences by age, symptom status, and duration of exposure. To account for additional study heterogeneity, we employed a beta-binomial model to pool SARs across studies and a negative-binomial model to estimate Robs. Results Households showed the highest transmission rates, with a pooled SAR of 21.1% (95% confidence interval [CI]:17.4–24.8). SARs were significantly higher where the duration of household exposure exceeded 5 days compared with exposure of ≤5 days. SARs related to contacts at social events with family and friends were higher than those for low-risk casual contacts (5.9% vs 1.2%). Estimates of SARs and Robs for asymptomatic index cases were approximately one-seventh, and for presymptomatic two-thirds of those for symptomatic index cases. We found some evidence for reduced transmission potential both from and to individuals younger than 20 years of age in the household context, which is more limited when examining all settings. Conclusions Our results suggest that exposure in settings with familiar contacts increases SARS-CoV-2 transmission potential. Additionally, the differences observed in transmissibility by index case symptom status and duration of exposure have important implications for control strategies, such as contact tracing, testing, and rapid isolation of cases. There were limited data to explore transmission patterns in workplaces, schools, and care homes, highlighting the need for further research in such settings.

Assessing recurrence of depression using a zero-inflated negative binomial model: A secondary analysis of lifelog data

2021 ◽  
Vol 300 ◽  
pp. 113919
Author(s):  
Narimasa Kumagai ◽  
Aran Tajika ◽  
Akio Hasegawa ◽  
Nao Kawanishi ◽  
Hirokazu Fujita ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Secondary Analysis ◽  
Negative Binomial Model ◽  
Binomial Model

scholarly journals Ruin problems in Markov-modulated risk models

2017 ◽  
Vol 12 (1) ◽  
pp. 23-48 ◽  
Author(s):  
David C.M. Dickson ◽  
Marjan Qazvini
Keyword(s):  
Continuous Time ◽  
Risk Model ◽  
Numerical Algorithms ◽  
Binomial Model ◽  
Risk Models ◽  
Time Of Ruin ◽  
Compound Binomial ◽  
Compound Binomial Model ◽  
Markov Modulated ◽  
The Time Of Ruin

AbstractChen et al. (2014), studied a discrete semi-Markov risk model that covers existing risk models such as the compound binomial model and the compound Markov binomial model. We consider their model and build numerical algorithms that provide approximations to the probability of ultimate ruin and the probability and severity of ruin in a continuous time two-state Markov-modulated risk model. We then study the finite time ruin probability for a discrete m-state model and show how we can approximate the density of the time of ruin in a continuous time Markov-modulated model with more than two states.

F-Test Alternatives to Fisher’s Exact Test and to the Chi-Square Test of Homogeneity in 2 × 2 Tables

1983 ◽  
Vol 8 (1) ◽  
pp. 59-73 ◽  
Author(s):  
John E. Overall ◽  
Robert R. Starbuck
Keyword(s):  
Beta Distribution ◽  
Binary Response ◽  
Binomial Model ◽  
Chi Square ◽  
Exact Probability ◽  
Exact Test ◽  
Mutual Dependence ◽  
Treatment Groups ◽  
Test Of Homogeneity ◽  
Chi Square Test

A binomial model is proposed for testing the significance of differences in binary response probabilities in two independent treatment groups. Without correction for continuity, the binomial statistic is essentially equivalent to Fisher’s exact probability. With correction for continuity, the binomial statistic approaches Pearson’s chi-square. Due to mutual dependence of the binomial and F distributions on the beta distribution, a simple F statistic can be used for computation instead of the binomial.

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