Topics in Circular Statistics

By S. Jammalamadaka, Ashis SenGupta. 2001

1,605 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

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Citations in the corpus

Hidden Markov models for circular and linear-circular time series (2006, background): “Specifically, if φ(x; µ, σ) is the density of the normal distribution, then the density of WN(µ, ρ) is given by (cf. Jammalamadaka and SenGupta 2001, p. 44) φw(θ ; µ, ρ) = ∑ n∈Z φ(θ + 2πn; µ, σ) .”
Asymmetric circular-linear multivariate regression models with applications to environmental data (2006, methodology): “Some expository literature on regression with directional data exist, e.g see the monographs by Jammalamadaka and SenGupta (2001), Mardia and Jupp (2000) and Batschelet (1981).”
The generalized von Mises distribution (2007, background): “For more details about WαSdistributions and inference, refer to [5,6].”
A Note on the Phase Locking Value and its Properties (2013, methodology): “The von Mises distribution is the most widely used model for circular (or periodic) random variables, in part because it is the circular distribution with maximum entropy subject to constraints on its first trigonometric moments (Jammalamadaka and Sengupta, 2001).”
Exploring wind direction and SO2 concentration by circular–linear density estimation (2012, background): “In the circular case, that is, for obtaining ϕ̂(·), Maximum Likelihood approaches are also possible (see Jammalamadaka and SenGupta (2001), Chapter 4).”
Estimating overlap of daily activity patterns from camera trap data (2009, methodology): “|) and the angular distance between the points is then d(x, xi) = 1 − cos[a(x, xi)], (Jammalamadaka and SenGupta, 2001, p. 17).”
On the challenge of treating various types of variables: application for improving the measurement of functional diversity (2009, background): “For example, Jammalamadaka and SenGupta (2001) presented the following two distances: d0(a; b) min(a b; 2p (a b)) p jp ja bjj (6) d(a; b) 1 cos(a b) (7) where a and b are given in Fig.”
Local polynomial regression for circular predictors (2009, background): “Recent accounts are given by Jammalamadaka & SenGupta (2001) and Mardia & Jupp (1999).”
A Bayesian Analysis of Directional Data Using the von Mises–Fisher Distribution (2005, methodology): “For a survey from the frequentist perspective the reader is referred to Fisher et al. (1987), Mardia (1972), and more recently, to Mardia and Jupp (2000), and Jammalamadaka and SenGupta (2001).”
Path tortuosity and the permeability of roads and trails to wolf movement (2004, methodology): “Because directions are circular in nature (e.g., 370 degrees equals 10 degrees), we programmed the computer to adjust the residuals such that they lay between + 180 degrees (Jammalamadaka and SenGupta 2001).”
The Astropy Project: Building an Open-science Project and Status of the v2.0 Core Package (2018, methodology): “A set of circular statistical estimators based on Jammalamadaka & Sengupta (2001) are implemented in astropy.stats .”
Minimal tool set for a prokaryotic circadian clock (2016, methodology): “Similarity between two circadian expression programs was established 341 using the circular correlation coefficient ρccc as described by Jammalamadaka and Sarma [108] applied 342 to estimated peak expression phases.”
A Family of Distributions on the Circle With Links to, and Applications Arising From, Möbius Transformation (2010, methodology): “Further properties of the proposed model are obtained, many by applying the theory of Möbius transformation.”