Estimating Population Size of Criminals: A New Horvitz–Thompson Estimator under One-Inflated Positive Poisson–Lindley Model

2021 ◽  
pp. 001112872110141
Author(s):  
Razik Ridzuan Mohd Tajuddin ◽  
Noriszura Ismail ◽  
Kamarulzaman Ibrahim
Keyword(s):  
Confidence Interval ◽  
Population Size ◽  
Simulation Study ◽  
Precise Estimate ◽  
Hidden Population

Many crime datasets often display an excess of “1” counts, arises when arrested criminals have the desire and ability to avoid subsequent arrests. In this study, a new Horvitz–Thompson (HT) estimator under one-inflated positive Poisson–Lindley (OIPPL) distribution which allow for one-inflation and the existence of heterogeneity in the data is developed to estimate the hidden population size of criminals. From the simulation study and applications to real crime datasets, the OIPPL is capable to provide an adequate fit to the datasets considered and the proposed HT estimator is found to produce a more precise estimate of the population size with a narrower 95% confidence interval as compared to several other contending estimators considered in this study.

scholarly journals Simplified large African carnivore density estimators from track indices

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2662 ◽  
Author(s):  
Christiaan W. Winterbach ◽  
Sam M. Ferreira ◽  
Paul J. Funston ◽  
Michael J. Somers
Keyword(s):  
Linear Regression ◽  
Confidence Interval ◽  
Population Size ◽  
Linear Model ◽  
Standard Error ◽  
Linear Models ◽  
Information Criteria ◽  
Large Carnivores ◽  
Simple Linear Regression ◽  
Akaike Information Criteria

BackgroundThe range, population size and trend of large carnivores are important parameters to assess their status globally and to plan conservation strategies. One can use linear models to assess population size and trends of large carnivores from track-based surveys on suitable substrates. The conventional approach of a linear model with intercept may not intercept at zero, but may fit the data better than linear model through the origin. We assess whether a linear regression through the origin is more appropriate than a linear regression with intercept to model large African carnivore densities and track indices.MethodsWe did simple linear regression with intercept analysis and simple linear regression through the origin and used the confidence interval for ß in the linear modely = αx + ß, Standard Error of Estimate, Mean Squares Residual and Akaike Information Criteria to evaluate the models.ResultsThe Lion on Clay and Low Density on Sand models with intercept were not significant (P > 0.05). The other four models with intercept and the six models thorough origin were all significant (P < 0.05). The models using linear regression with intercept all included zero in the confidence interval for ß and the null hypothesis that ß = 0 could not be rejected. All models showed that the linear model through the origin provided a better fit than the linear model with intercept, as indicated by the Standard Error of Estimate and Mean Square Residuals. Akaike Information Criteria showed that linear models through the origin were better and that none of the linear models with intercept had substantial support.DiscussionOur results showed that linear regression through the origin is justified over the more typical linear regression with intercept for all models we tested. A general model can be used to estimate large carnivore densities from track densities across species and study areas. The formulaobserved track density = 3.26 × carnivore densitycan be used to estimate densities of large African carnivores using track counts on sandy substrates in areas where carnivore densities are 0.27 carnivores/100 km2or higher. To improve the current models, we need independent data to validate the models and data to test for non-linear relationship between track indices and true density at low densities.

Estimation of the parameters of a branching process from migrating binomial observations

1998 ◽  
Vol 30 (4) ◽  
pp. 948-967 ◽  
Author(s):  
C. Jacob ◽  
J. Peccoud
Keyword(s):  
Confidence Interval ◽  
Asymptotic Behaviour ◽  
Population Size ◽  
Branching Process ◽  
Total Population ◽  
Initial Population ◽  
Asymptotic Confidence Interval ◽  
Total Population Size ◽  
Initial Population Size ◽  
Watson Process

This paper considers a branching process generated by an offspring distribution F with mean m < ∞ and variance σ2 < ∞ and such that, at each generation n, there is an observed δ-migration, according to a binomial law Bpvn*Nnbef which depends on the total population size Nnbef. The δ-migration is defined as an emigration, an immigration or a null migration, depending on the value of δ, which is assumed constant throughout the different generations. The process with δ-migration is a generation-dependent Galton-Watson process, whereas the observed process is not in general a martingale. Under the assumption that the process with δ-migration is supercritical, we generalize for the observed migrating process the results relative to the Galton-Watson supercritical case that concern the asymptotic behaviour of the process and the estimation of m and σ2, as n → ∞. Moreover, an asymptotic confidence interval of the initial population size is given.

scholarly journals A Simulation Study on Increasing Capture Periods in Bayesian Closed Population Capture-Recapture Models with Heterogeneity

2020 ◽  
Vol 18 (1) ◽  
pp. 2-23
Author(s):  
Ross M. Gosky ◽  
Joel Sanqui
Keyword(s):  
Population Size ◽  
Simulation Study ◽  
Simulated Data ◽  
Population Models ◽  
Data Set ◽  
Closed Population ◽  
Population Sizes ◽  
Capture Recapture

Capture-Recapture models are useful in estimating unknown population sizes. A common modeling challenge for closed population models involves modeling unequal animal catchability in each capture period, referred to as animal heterogeneity. Inference about population size N is dependent on the assumed distribution of animal capture probabilities in the population, and that different models can fit a data set equally well but provide contradictory inferences about N. Three common Bayesian Capture-Recapture heterogeneity models are studied with simulated data to study the prevalence of contradictory inferences is in different population sizes with relatively low capture probabilities, specifically at different numbers of capture periods in the study.

Simulation Study of Truck Traffic at Single-Lane Roundabouts with and without Slip Lanes

2015 ◽  
Vol 2517 (1) ◽  
pp. 80-86
Author(s):  
Majed Al-Ghandour
Keyword(s):  
Confidence Interval ◽  
Simulation Study ◽  
Free Flow ◽  
Nonlinear Relationship ◽  
Truck Traffic ◽  
Average Delay ◽  
Left Turn ◽  
Delay Performance ◽  
Traffic Volumes ◽  
Total Average

As transportation planners and engineers design useful and effective roundabouts, these professionals are challenged by the need to accommodate safely truck traffic and high truck volumes in particular. Delay is a major challenge with truck traffic, especially with returning left-turning trucks. The delay performance of single-lane roundabouts with an adjacent slip lane for right turns was considered under various truck traffic percentages and two slip lane exit types (free flow and yield). A microsimulation assessment compared four percentages of right-turn truck traffic: 0% (no trucks), 5%, 45%, and 80%. Results indicate that the average delay of a roundabout with a slip lane under various truck traffic percentages is a nonlinear relationship with slip lane volumes and is sensitive to changes in truck traffic percentages before oversaturation is reached. As expected, results indicate that a free-flow slip lane exit type significantly reduces total average delay in roundabouts compared with having no slip lane with truck traffic. Yield slip lane exit types also reduced total average delay from truck traffic in roundabouts, but to a lesser degree than free-flow slip lane exit types. At higher truck traffic volumes, overall average roundabout delay decreased 15% (estimated VISSIM 95% confidence interval of reduction estimated between —16% and —2%) with a free-flow slip lane exit type. Finally, returning left-turn trucks increased total roundabout average delay significantly, by 64%.

scholarly journals Modelling the abundance of grey seals (Halichoerus grypus) along the Norwegian coast

2012 ◽  
Vol 69 (8) ◽  
pp. 1436-1447 ◽  
Author(s):  
Tor Arne Øigård ◽  
Anne Kirstine Frie ◽  
Kjell Tormod Nilssen ◽  
Mike Osborne Hammill
Keyword(s):  
Confidence Interval ◽  
Population Size ◽  
Halichoerus Grypus ◽  
Grey Seal ◽  
Norwegian Coast ◽  
Structured Population ◽  
Population Dynamics Model ◽  
Level Model ◽  
Age Structured ◽  
The Uk

Abstract Øigård, T. A., Frie, A. K., Nilssen, K. T., and Hammill, M. O. 2012. Modelling the abundance of grey seals (Halichoerus grypus) along the Norwegian coast. – ICES Journal of Marine Science, 69: . An age-structured population dynamics model of the Norwegian grey seal (Halichoerus grypus) population has been developed. The model is of a Bayesian character in the sense that priors for various parameters were used. Model runs indicated an increase in the abundance of the total Norwegian grey seal population during the last 30 years, suggesting a total of 8740 (95% confidence interval: 7320–10 170) animals in 2011. A total catch of 707 (95% confidence interval: 532–882) grey seals would maintain the population size at the 2011 level. Model runs suggest that current catch levels will likely result in a reduction in the population size in Sør-Trøndelag and Nord-Trøndelag counties, and an increase in the population size in Rogaland, Nordland, Troms, and Finnmark counties. The model runs assumed that 80% of the seals taken in Rogaland came from the UK and that 50 and 55% of the catches in Troms and Finnmark, respectively, were immigrants from Russia.

scholarly journals Estimating hidden population size using Respondent-Driven Sampling data

2014 ◽  
Vol 8 (1) ◽  
pp. 1491-1521 ◽  
Author(s):  
Mark S. Handcock ◽  
Krista J. Gile ◽  
Corinne M. Mar
Keyword(s):  
Population Size ◽  
Respondent Driven Sampling ◽  
Hidden Population

scholarly journals Sociodemographic Indicators of Child and Adolescent Mortality in Finland—A Nationwide Study of 310 Municipalities Covering Over 5,000,000 Inhabitants

2021 ◽  
Vol 9 ◽  
Author(s):  
Petteri Oura ◽  
Antti Sajantila
Keyword(s):  
Mortality Rate ◽  
Population Density ◽  
Confidence Interval ◽  
Foreign Language ◽  
Population Size ◽  
Divorce Rate ◽  
Premature Mortality ◽  
Child And Adolescent ◽  
Median Income ◽  
Sociodemographic Indicators

Background: The reduction of child and adolescent deaths (defined as decedents aged 0–19 years) remains a crucial public health priority also in high-income countries such as Finland. There is evidence of a relationship between socioeconomic gradients and child mortality, but the association is considered complex and relatively poorly understood. Exploiting a Finnish dataset with nationwide coverage, the present study aimed to shed light on the sociodemographic predictors of child and adolescent mortality at the municipality level.Methods: A public database of Statistics Finland was queried for municipality-level data on sociodemographic traits and child and adolescent deaths in Finland during the years 2011–2018. The sociodemographic indicators included total population size, child and adolescent population size, sex distribution, mean age, education, unemployment, median income, population density, rurality, percentage of individuals living in their birth municipality, household size, overcrowded households, foreign language speakers, divorce rate, car ownership rate, and crime rate. The sociodemographic indicators were modeled against child and adolescent mortality by means of generalized estimating equations.Results: A total of 2,371 child and adolescent deaths occurred during the 8-year study period, yielding an average annual mortality rate of 26.7 per 100,000 individuals. Despite a fluctuating trend, the average annual decline in child and adolescent deaths was estimated to be 3% (95% confidence interval 1–5%). Of the sociodemographic indicators, population density was associated with higher child and adolescent mortality (rate ratio 1.03, 95% confidence interval 1.01–1.06), whereas the percentage of foreign language speakers was associated with lower child and adolescent mortality (0.96, 0.93–0.99).Conclusion: Densely populated areas should be the primary focus of efforts to reduce child and adolescent mortality. Of note is also the apparently protective effect of foreign language speakers for premature mortality. Future studies are welcomed to scrutinize the mediating pathways and individual-level factors behind the associations detected in this study.

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