17 citations · 23 across the 5 of their papers we have counts for
11 papers
An Empirical Study of the Occurrence of Heavy-Tails in Training a ReLU Gate
Sayar Karmakar, Anirbit Mukherjee
A particular direction of recent advance about stochastic deep-learning algorithms has been about uncovering a rather mysterious heavy-tailed nature of the stationary distribution…
Long-term prediction intervals with many covariates
Sayar Karmakar, Marek Chudy, Wei Biao Wu
Accurate forecasting is one of the fundamental focus in the literature of econometric time-series. Often practitioners and policy makers want to predict outcomes of an entire time…
Simultaneous inference for time-varying models
Sayar Karmakar, Stefan Richter, Wei Biao Wu
A general class of time-varying regression models is considered in this paper. We estimate the regression coefficients by using local linear M-estimation. For these estimators, wea…
Time-varying auto-regressive models for count time-series
Arkaprava Roy, Sayar Karmakar
Count-valued time series data are routinely collected in many application areas. We are particularly motivated to study the count time series of daily new cases, arising from COVID…
Bayesian modelling of time-varying conditional heteroscedasticity
Sayar Karmakar, Arkaprava Roy
Conditional heteroscedastic (CH) models are routinely used to analyze financial datasets. The classical models such as ARCH-GARCH with time-invariant coefficients are often inadequ…
Evaluating the Impact of COVID-19 on Cyberbullying through Bayesian Trend Analysis
Sayar Karmakar, Sanchari Das
COVID-19's impact has surpassed from personal and global health to our social life. In terms of digital presence, it is speculated that during pandemic, there has been a significan…