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pro vyhledávání: '"S. C. Pandhare"'
Autor:
S. C. Pandhare, T. V. Ramanathan
Publikováno v:
Australian & New Zealand Journal of Statistics. 62:485-507
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::29e86750f778fc52e769a572d9558b6e
https://doi.org/10.1111/anzs.12310
https://doi.org/10.1111/anzs.12310
Autor:
S. C. Pandhare, T. V. Ramanathan
Publikováno v:
Statistical Inference for Stochastic Processes. 23:637-663
Claeskens and Hjort (J Am Stat Assoc 98(464):900–916, 2003) constructed the focused information criterion (FIC) using maximum likelihood estimators to facilitate the contextual selection of probability models for independently distributed observati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::866586260873e6dd487fb6289b857917
https://doi.org/10.1007/s11203-020-09208-2
https://doi.org/10.1007/s11203-020-09208-2
Autor:
S. C. Pandhare, T. V. Ramanathan
The classical lasso estimation for sparse, high-dimensional regression models is typically biased and lacks the oracle properties. The desparsified versions of the lasso have been proposed in the literature that attempt to overcome these drawbacks. I
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8680be4c5fd4d6ec16cf8463bc4ff392
Autor:
S. C. Pandhare, T. V. Ramanathan
Publikováno v:
Journal of Statistical Theory and Practice. 15
Statistical modeling of biomedical data arising from the cytologic samples collected during cancer trials often involves the analysis of binary time series responses indicating the status of the samples being benign or malignant. The model selection
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f6eba22aa780f617146f4f6b3185d22e
https://doi.org/10.1007/s42519-021-00169-0
https://doi.org/10.1007/s42519-021-00169-0