Liberal Arts and Sciences
Khare Lab
Led by Kshitij Khare · Statistics
What we study
The Khare Lab studies advanced statistical methods, including Bayesian inference and Markov chain Monte Carlo, with applications in macroeconomics and interdisciplinary projects in fields like chemistry and neuroscience.
What working here is like
- Computational
- No organisms (data only)
- Coding required
- Papers
- 5
Recent papers, explained
- Graphical Model Selection to Infer the Partial Correlation Network of Allelic Effects in Genomic Prediction With an Application in Dairy Cattle
2025 · Journal of Animal Breeding and Genetics
Develops methods to estimate partial correlation networks in genomic prediction.
- Posterior consistency in multi-response regression models with non-informative priors for the error covariance matrix in growing dimensions
2025 · Bernoulli
Investigates posterior consistency of covariance matrix priors in high dimensions.
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- Recurrence and transience of a Markov chain on $\mathbb Z$ + and evaluation of prior distributions for a Poisson mean
2024 · Journal of Applied Probability
Studies Markov chains to evaluate improper prior distributions in Poisson models.
- Estimation of Gaussian directed acyclic graphs using partial ordering information with applications to DREAM3 networks and dairy cattle data
2023 · The Annals of Applied Statistics
Develops a method to estimate directed acyclic graphs with partial ordering.
- The Bayesian nested lasso for mixed frequency regression models
2023 · The Annals of Applied Statistics
Creates a Bayesian nested lasso to estimate lags in mixed-frequency models.
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How to reach out
Kshitij Khare hasn't set up this page yet. Their UF Scholars profile lists their publications.