Showing items with similar title or keywords.

• Bayesian semiparametric long memory models for discretized event data 

  Chakraborty, Antik; Ovaskainen, Otso; Dunson, David B. (Institute of Mathematical Statistics, 2022)

  We introduce a new class of semiparametric latent variable models for long memory discretized event data. The proposed methodology is motivated by a study of bird vocalizations in the Amazon rain forest; the timings of ...

• Statistical methods for adaptive river basin management and monitoring 

  Kotamäki, Niina (University of Jyväskylä, 2018)

  Decision-making at different phases of adaptive river basin management planning rely largely on the information that is gained through environmental monitoring. The aim of this thesis was to develop and test statistical ...

• Can visualization alleviate dichotomous thinking : Effects of visual representations on the cliff effect 

  Helske, Jouni; Helske, Satu; Cooper, Matthew; Ynnerman, Anders; Besancon, Lonni (IEEE, 2021)

  Common reporting styles for statistical results in scientific articles, such as \pvalues\ and confidence intervals (CI), have been reported to be prone to dichotomous interpretations, especially with respect to the null ...

• Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo 

  Vihola, Matti; Helske, Jouni; Franks, Jordan (Wiley-Blackwell, 2020)

  We consider importance sampling (IS) type weighted estimators based on Markov chain Monte Carlo (MCMC) targeting an approximate marginal of the target distribution. In the context of Bayesian latent variable models, the ...

• Identifying territories using presence-only citizen science data : An application to the Finnish wolf population 

  Karppinen, Santeri; Rajala, Tuomas; Mäntyniemi, Samu; Kojola, Ilpo; Vihola, Matti (Elsevier BV, 2022)

  Citizens, community groups and local institutions participate in voluntary biological monitoring of population status and trends by providing species data e.g. for regulations and conservation. Sophisticated statistical ...