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Nalini Ravishanker
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2020 – today
- 2024
- [j13]Namitha Pais, Nalini Ravishanker, Sanguthevar Rajasekaran:
Supervised Dynamic Correlated Topic Model for Classifying Categorical Time Series. Algorithms 17(7): 275 (2024) - [j12]Patrick Toman, Nalini Ravishanker, Nathan Lally, Sanguthevar Rajasekaran:
Latent Autoregressive Student-t Prior Process Models to Assess Impact of Interventions in Time Series. Future Internet 16(1): 8 (2024) - 2023
- [j11]Guanyu Hu, Ming-Hui Chen, Nalini Ravishanker:
Bayesian analysis of spherically parameterized dynamic multivariate stochastic volatility models. Comput. Stat. 38(2): 845-869 (2023) - [j10]Renjie Chen, Nalini Ravishanker:
Feature Construction Using Persistence Landscapes for Clustering Noisy IoT Time Series. Future Internet 15(6): 195 (2023) - [c4]Patrick Toman, Ahmed Soliman, Nalini Ravishanker, Sanguthevar Rajasekaran, Nathan Lally, Hunter D'Addeo:
Understanding Insured Behavior through Causal Impact Analysis of IoT Streams. ISCSIC 2023: 349-357 - 2022
- [j9]Katiane S. Conceição, Marinho Gomes Andrade, Francisco Louzada, Nalini Ravishanker:
Characterizations and generalizations of the negative binomial distribution. Comput. Stat. 37(3): 1255-1286 (2022) - [j8]Haitao Liu, Jian Zou, Nalini Ravishanker:
Biclustering high-frequency financial time series based on information theory. Stat. Anal. Data Min. 15(4): 447-462 (2022) - 2021
- [j7]Dipak K. Dey, Junfeng Liu, Nalini Ravishanker, Edwards Qiang Zhang:
A note on response mean confidence band for linear regression models. Commun. Stat. Simul. Comput. 50(3): 778-785 (2021) - [c3]Ahmed Soliman, Sanguthevar Rajasekaran, Patrick Toman, Nalini Ravishanker, Nathan Lally, Hunter D'Addeo:
A Custom Unsupervised Approach for Pipe-Freeze Online Anomaly Detection. WF-IoT 2021: 663-668 - 2020
- [i3]Paul A. Parker, Scott H. Holan, Nalini Ravishanker:
Nonlinear Time Series Classification Using Bispectrum-based Deep Convolutional Neural Networks. CoRR abs/2003.02353 (2020)
2010 – 2019
- 2019
- [j6]Yaohua Zhang, Jian Zou, Nalini Ravishanker, Aerambamoorthy Thavaneswaran:
Modeling financial durations using penalized estimating functions. Comput. Stat. Data Anal. 131: 145-158 (2019) - [c2]Zigeng Wang, Abdullah-Al Mamun, Xingyu Cai, Nalini Ravishanker, Sanguthevar Rajasekaran:
Efficient Sequential and Parallel Algorithms for Estimating Higher Order Spectra. CIKM 2019: 1743-1752 - [c1]Aerambamoorthy Thavaneswaran, Ruppa K. Thulasiram, Zimo Zhu, Mohammed Erfanul Hoque, Nalini Ravishanker:
Fuzzy Value-at-Risk Forecasts Using a Novel Data-Driven Neuro Volatility Predictive Model. COMPSAC (2) 2019: 221-226 - [i2]Renjie Chen, Jingyue Zhang, Nalini Ravishanker, Karthik Konduri:
Clustering Activity-Travel Behavior Time Series using Topological Data Analysis. CoRR abs/1907.07603 (2019) - 2018
- [i1]Abdullah-Al Mamun, Zigeng Wang, Xingyu Cai, Nalini Ravishanker, Sanguthevar Rajasekaran:
Efficient Sequential and Parallel Algorithms for Estimating Higher Order Spectra. CoRR abs/1805.11775 (2018) - 2013
- [j5]Jane L. Harvill, Nalini Ravishanker, Bonnie K. Ray:
Bispectral-based methods for clustering time series. Comput. Stat. Data Anal. 64: 113-131 (2013)
2000 – 2009
- 2009
- [j4]Jeffrey Pai, Nalini Ravishanker:
Maximum likelihood estimation in vector long memory processes via EM algorithm. Comput. Stat. Data Anal. 53(12): 4133-4142 (2009) - 2008
- [j3]Nalini Ravishanker, Zhaohui Liu, Bonnie K. Ray:
NHPP models with Markov switching for software reliability. Comput. Stat. Data Anal. 52(8): 3988-3999 (2008) - 2006
- [j2]Bonnie K. Ray, Zhaohui Liu, Nalini Ravishanker:
Dynamic Reliability Models for Software Using Time-Dependent Covariates. Technometrics 48(1): 1-10 (2006) - 2004
- [j1]Nalini Ravishanker:
Survival Analysis. Technometrics 46(1): 111-112 (2004)
Coauthor Index
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