Saptarshi Chakraborty

Saptarshi Chakraborty
Memorial Sloan Kettering Cancer Center | MSKCC · Epidemiology & Biostatistics

Doctor of Philosophy

About

12
Publications
592
Reads
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91
Citations
Citations since 2016
12 Research Items
91 Citations
20162017201820192020202120220510152025
20162017201820192020202120220510152025
20162017201820192020202120220510152025
20162017201820192020202120220510152025
Additional affiliations
August 2013 - August 2018
University of Florida
Position
  • Graduate Assistant

Publications

Publications (12)
Article
We establish asymptotic normality of the batch means estimator of MCMC variance for reversible geometrically ergodic chains. Existing results use assumptions which are not feasible for most statistical MCMC applications. Practical utility of the result is demonstrated through numerical examples.
Article
Full-text available
The vast preponderance of somatic mutations in a typical cancer are either extremely rare or have never been previously recorded in available databases that track somatic mutations. These constitute a hidden genome that contrasts the relatively small number of mutations that occur frequently, the properties of which have been studied in depth. Here...
Article
It is increasingly common clinically for cancer specimens to be examined using techniques that identify somatic mutations. In principle these mutational profiles can be used to diagnose the tissue of origin, a critical task for the 3-5% of tumors that have an unknown primary site. Diagnosis of primary site is also critical for screening tests that...
Preprint
It is increasingly common clinically for cancer specimens to be examined using techniques that identify somatic mutations. In principle these mutational profiles can be used to diagnose the tissue of origin, a critical task for the 3-5% of tumors that have an unknown primary site. Diagnosis of primary site is also critical for screening tests that...
Article
Full-text available
To date, the vast preponderance of somatic variants observed in the cancer genome have been rare variants, and it is common in practice to encounter in a new tumor variants that have not been observed previously. Here we focus on probability estimation for encountering such hitherto unseen variants. We draw upon statistical methodology that has bee...
Preprint
The batch means estimator of the MCMC variance is a simple and effective measure of accuracy for MCMC based ergodic averages. Under various regularity conditions, the estimator has been shown to be consistent for the true variance. However, the estimator can be unstable in practice as it depends directly on the raw MCMC output. A measure of accurac...
Article
Objective: In response to rising national health expenditures, the Patient Protection and Affordable Care Act (ACA) was passed in 2010, with major provisions implemented in 2014. Due to increasing concerns about workload and compensation among neurosurgeons, we evaluated trends in neurosurgical reimbursement, productivity and compensation before a...
Article
Full-text available
This paper studies circular correlations for the bivariate von Mises sine and cosine distributions. These are two simple and appealing models for bivariate angular data with five parameters each that have interpretations comparable to those in the ordinary bivariate normal model. However, the variability and association of the angle pairs cannot be...
Article
Markov chain Monte Carlo is widely used in a variety of scientific applications to generate approximate samples from intractable distributions. A thorough understanding of the convergence and mixing properties of these Markov chains can be obtained by studying the spectrum of the associated Markov operator. While several methods to bound/estimate t...
Article
Full-text available
Statistical analyses of directional or angular data have applications in a variety of fields, such as geology, meteorology and bioinformatics. There is substantial literature on descriptive and inferential techniques for univariate angular data, with the bivariate (or more generally, multivariate) cases receiving more attention in recent years. How...
Article
OBJECTIVE The American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) universal Surgical Risk Calculator is an online decision-support tool that uses patient characteristics to estimate the risk of adverse postoperative events. Further validation of this risk calculator in the neurosurgical population is needed; the...
Article
Full-text available
The Bayesian probit regression model (Albert and Chib (1993)) is popular and widely used for binary regression. While the improper flat prior for the regression coefficients is an appropriate choice in the absence of any prior information, a proper normal prior is desirable when prior information is available or in modern high dimensional settings...

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