Aila Särkkä
Mina forskningsområden är spatial statistik och spatio-temporal modellering. Mycket av min tidigare forskning har varit inom Gibbs punktprocesser, till exempel pseudo-likelihood uppskattning av parametrar och konstruktion av nya modeller. Jag har också arbetat med spatio-temporala modeller och utvecklat uppskattningsmetoder för spatio-temporala data. Numera jobbar jag mest med 3D-mikroskopdata med replikater. Den största utmaningen är att hantera punktprocessdata som är heterogen och icke-isotropisk. Mina huvudsakliga tillämpningsområden är materialvetenskap och neurologi.
Visar 63 publikationer
Plant size inequality: How to analyse competing spatial dissimilarity Indices?
Statistical modeling of diabetic neuropathy: Exploring the dynamics of nerve mortality
Hierarchical log Gaussian Cox process for regeneration in uneven-aged forests
Tests for isotropy in spatial point patterns – A comparison of statistical indices
Pairwise interaction Markov model for 3D epidermal nerve fibre endings
Spatial modeling of epidermal nerve fiber patterns
Tessellation-based stochastic modelling of 3D coating structures imaged with FIB-SEM tomography
Stochastic modelling of 3D fiber structures imaged with X-ray microtomography
Point process models for sweat gland activation observed with noise
Marked point process analysis of epidermal nerve fibres
Second order analysis of geometric anisotropic point processes revisited
A Bayesian hierarchical point process model for epidermal nerve fiber patterns
Raster Image Correlation Spectroscopy Performance Evaluation
Colloidal particle aggregation in three dimensions
Single particle raster image analysis of diffusion for particle mixtures
A review on anisotropy analysis of spatial point patterns
Hierarchical models for epidermal nerve fiber data
Single particle raster image analysis of diffusion
A three-dimensional anisotropic point process characterization for pharmaceutical coatings
Estimating geometric anisotropy in spatial point patterns
Characterization of pore structure of polymer blended films used for controlled drug release
From static micrographs to particle aggregation dynamics in three dimensions
Discovering early diabetic neuropathy from epidermal nerve fiber patterns
What we look at in paintings: A comparison between experienced and inexperienced art viewers
Variational Bayes approach for classification of points in superpositions of point processes
Statistical Prediction of Global Sea Level From Global Temperature
Classification of Points in Superpositions of Strauss and Poisson Processes
Identifying directional persistence in intracellular particle motion using Hidden Markov Models
Hierarchical second-order analysis of replicated spatial point patterns with non-spatial covariates
Assessing the Uncertainty in Projecting Local Mean Sea Level from Global Temperature
Parameter estimation for growth interaction processes using spatio-temporal information
What mark variograms tell about spatial plant interactions
Automatic Particle Detection in Microscopy Using Temporal Correlations
Self-calibrated concentration measurements of polydisperse nanoparticles
Development and evaluation of spatial point process models for epidermal nerve fibers
Analysis of spatial structure of epidermal nerve entry point patterns based on replicated data
Some edge correction methods for marked spatio-temporal point process models
Second-order spatial analysis of epidermal nerve fibers
A third order point process characteristic for multi-type point processes
Modelling tree roots in mixed forest stands by inhomogeneous marked Gibbs point processes.
Anisotropy analysis of pressed point processes
Modeling the microstructure of sintered copper
Modelling growth of trees by space-time growth-interaction processe
The analysis of marked point patterns evolving through space and time
An additive edge correction for the influence potential of trees
Some space-time interaction models for marked point processes.
An additive edge correction based on the refined Campbell theorem
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Visar 6 forskningsprojekt
Inference in the face of intractability: Bayesian applications of continuous-time Markov processes
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