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The number of species can be estimated by sampling individuals from a species assemblage. The problem of estimating generalized species accumulation curve is addressed in a nonparametric Poisson mixture model. A likelihood-based estimator…

Statistics Theory · Mathematics 2007-06-13 Chang Xuan Mao

While non-invasive sampling is more and more commonly used in capture-recapture (CR) experiments, it carries a higher risk of misidentifications than direct observations. As a consequence, one must screen the data to retain only the…

Quantitative Methods · Quantitative Biology 2023-04-04 Rémi Fraysse , Rémi Choquet , Carlo Costantini , Roger Pradel

We consider the problem of learning two families of time-evolving random measures from indirect observations. In the first model, the signal is a Fleming--Viot diffusion, which is reversible with respect to the law of a Dirichlet process,…

Statistics Theory · Mathematics 2014-11-19 Omiros Papaspiliopoulos , Matteo Ruggiero , Dario Spanò

Given a sequence of observations from a discrete-time, finite-state hidden Markov model, we would like to estimate the sampling distribution of a statistic. The bootstrap method is employed to approximate the confidence regions of a…

Computation · Statistics 2009-09-29 Cheng-Der Fuh , Inchi Hu

We generalize the approach of Liu and Lawrence (1999) for multiple changepoint problems where the number of changepoints is unknown. The approach is based on dynamic programming recursion for efficient calculation of the marginal…

Computation · Statistics 2009-09-29 Heng Lian

In the broadcasting problem on trees, a $\{-1,1\}$-message originating in an unknown node is passed along the tree with a certain error probability $q$. The goal is to estimate the original message without knowing the order in which the…

Probability · Mathematics 2025-09-12 Ernst Althaus , Lisa Hartung , Rebecca Steiner

Multiple systems estimation strategies have recently been applied to quantify hard-to-reach populations, particularly when estimating the number of victims of human trafficking and modern slavery. In such contexts, it is not uncommon to see…

Methodology · Statistics 2020-03-06 Lax Chan , Bernard W. Silverman , Kyle Vincent

With the internet, a massive amount of information on species abundance can be collected under citizen science programs. However, these data are often difficult to use directly in statistical inference, as their collection is generally…

Applications · Statistics 2015-02-27 Christophe Giraud , Clément Calenge , Camille Coron , Romain Julliard

There is a lack of methodological results for continuous time change detection due to the challenges of noninformative prior specification and efficient posterior inference in this setting. Most methodologies to date assume data are…

Methodology · Statistics 2025-04-28 Dan Cunha , Mark Friedl , Luis Carvalho

Consider the random Dirichlet partition of the interval into $n$ fragments with parameter $\theta >0$. We recall the unordered Ewens sampling formulae from finite Dirichlet partitions. As this is a key variable for estimation purposes,…

Methodology · Statistics 2008-09-25 Thierry Huillet , Christian Paroissin

We explore the use of a sufficient statistic based on the data of samples that are selected under the M_0 capture-recapture closed population model (Schwarz and Seber, 1999). A Rao-Blackwellized version of the estimator based on a…

Methodology · Statistics 2018-11-30 Kyle Vincent

This paper proposed a new method to estimate the missing data by using the filtering process. We used datasets without missing data and randomly missing data to evaluate the new method of estimation by using the Box - Jenkins modeling…

Methodology · Statistics 2008-11-06 R. Ahmad Mahir , A. M. H. Al-Khazaleh

This article presents a new method for estimating the amount of an artifact class in use at a given moment in the past from a random assemblage of archaeological finds. This method is based on the use of simulation, since an analytical…

Applications · Statistics 2019-08-01 Stephen A. Collins-Elliott

The random forest algorithm, proposed by L. Breiman in 2001, has been extremely successful as a general-purpose classification and regression method. The approach, which combines several randomized decision trees and aggregates their…

Statistics Theory · Mathematics 2015-11-19 Gérard Biau , Erwan Scornet

Capture-recapture methods for estimating the total size of elusive populations are widely-used, however, due to the choice of estimator impacting upon the results and conclusions made, the question of performance of each estimator is…

Methodology · Statistics 2023-12-15 Layna Charlie Dennett , Dankmar Böhning

Dead time effects have been considered a major limitation for fast data acquisition in various time-correlated single photon counting applications, since a commonly adopted approach for dead time mitigation is to operate in the low-flux…

Signal Processing · Electrical Eng. & Systems 2019-06-26 Joshua Rapp , Yanting Ma , Robin M. A. Dawson , Vivek K Goyal

The aim of the paper is to extend the model of "fishing problem". The simple formulation is following. The angler goes to fishing. He buys fishing ticket for a fixed time. There are two places for fishing at the lake. The fishes are caught…

Probability · Mathematics 2008-12-19 Anna Karpowicz , Krzysztof Szajowski

The broken random sample problem was first introduced by DeGroot, Feder, and Gole (1971, Ann. Math. Statist.): in each observation (batch), a random sample of $M$ i.i.d. point pairs $ ((X_i,Y_i))_{i=1}^M$ is drawn from a joint distribution…

Statistics Theory · Mathematics 2026-02-11 Hancheng Bi , Bernhard Schmitzer , Thilo D. Stier

Analyzing simple and natural price-adjustment processes that converge to a market equilibrium is a fundamental question in economics. Such an analysis may have implications in economic theory, computational economics, and distributed…

Computer Science and Game Theory · Computer Science 2015-04-21 Noa Avigdor-Elgrabli , Yuval Rabani , Gala Yadgar

A probabilistic query may not be estimable from observed data corrupted by missing values if the data are not missing at random (MAR). It is therefore of theoretical interest and practical importance to determine in principle whether a…

Machine Learning · Statistics 2016-11-16 Jin Tian