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researcher

N. Pillai

69 papers hereh-index 304k citations100 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author3
  • first author15
  • middle author28
  • last author23

Across the 69 of 69 papers where every author was matched, so the position is known.

fields
  • math.PR21
  • math.ST16
  • stat.ME16
  • stat.CO10
  • stat.AP3
  • cond-mat.soft1
same name
  • N. Pillai — 7 papers, h 5
  • N. Pillai — 4 papers, h 6
  • N. Pillai — 1 paper, h 2
  • N. Pillai — 1 paper, h 0

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20082026
most citedUniversality of covariance matrices

155 citations · 955 across the 56 of their papers we have counts for

collaborators
Showing 2013 · stat.MEShow all

4 papers · 2 filters

stat.ME2013★ 6 cited

Degrees of freedom for combining regression with factor analysis

Patrick O. Perry, Natesh S. Pillai

In the AGEMAP genomics study, researchers were interested in detecting genes related to age in a variety of tissue types. After not finding many age-related genes in some of the an…

stat.ME2013★ 4 cited

A location-mixture autoregressive model for online forecasting of lung tumor motion

Daniel Cervone, Natesh S. Pillai, Debdeep Pati +2

Lung tumor tracking for radiotherapy requires real-time, multiple-step ahead forecasting of a quasi-periodic time series recording instantaneous tumor locations. We introduce a loc…

stat.ME2013★ 46 cited

Bayesian Nonparametric Weighted Sampling Inference

Yajuan Si, Natesh S. Pillai, Andrew Gelman

It has historically been a challenge to perform Bayesian inference in a design-based survey context. The present paper develops a Bayesian model for sampling inference in the prese…

stat.ME2013★ 4 cited

Statistical Inference for Stochastic Differential Equations with Memory

Martin Lysy, Natesh S. Pillai

In this paper we construct a framework for doing statistical inference for discretely observed stochastic differential equations (SDEs) where the driving noise has 'memory'. Classi…

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