Tank, Fatih

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14411/11235
Name Variants
Tank, Fatih
T., Fatih
T., F.
Tank, F.
F. Tank
Fatih Tank
Job Title
Profesör Doktor
Email Address
fatih.tank@atilim.edu.tr
Main Affiliation
Status
Current Staff
Website
ORCID ID
0000-0003-3758-396X
Scopus Author ID
12041740200
Turkish CoHE Profile ID
19415
Google Scholar ID
WoS Researcher ID
W-4877-2017

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
0
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GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
1
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QUALITY EDUCATION4
QUALITY EDUCATION
0
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GENDER EQUALITY5
GENDER EQUALITY
0
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CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
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AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
0
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REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
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SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
0
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RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
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CLIMATE ACTION13
CLIMATE ACTION
0
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LIFE BELOW WATER14
LIFE BELOW WATER
0
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LIFE ON LAND15
LIFE ON LAND
0
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PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
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PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
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Documents

23

Citations

173

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7

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Documents

22

Citations

136

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Scholarly Output

8

Articles

7

Views / Downloads

37/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

72

Scopus Citation Count

88

Patents

0

Projects

0

WoS Citations per Publication

9.00

Scopus Citations per Publication

11.00

Open Access Source

1

Supervised Theses

0

JournalCount
Journal of Computational and Applied Mathematics2
Insurance: Mathematics and Economics1
Japanese Journal of Statistics and Data Science1
Applied Mathematics and Computation1
Statistical Papers1
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Author: Bhattacharjee, AtanuHas files: false

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    Article
    Afthd: Bayesian Accelerated Failure Time Model for High-Dimensional Time-To Data
    (Springernature, 2025) Kumari, Pragya; Bhattacharjee, Atanu; Vishwakarma, Gajendra K.; Tank, Fatih
    Analyzing high-dimensional (HD) data with time-to-event outcomes poses a formidable challenge. The accelerated failure time (AFT) model, an alternative to the Cox proportional hazard model in survival analysis, lacks sufficient R packages for HD time-to-event data under the Bayesian paradigm. To address this gap, we develop the R package afthd. This tool facilitates advanced AFT modeling, offering Bayesian analysis for univariate and multivariable scenarios. This work includes diagnostic plots and an open-source R code for working with HD data, extending the conventional AFT model to the Bayesian framework of log-normal, Weibull, and log-logistic AFT models. The methodology is rigorously validated through simulation techniques, yielding consistent results across parametric AFT models. The application part is also performed on two different real HD liver cancer datasets, which reveals the proposed method's significance by obtaining inferences for survival estimates for the disease. Our developed package afthd is competent in working with HD time-to-event data using the conventional AFT model along with the Bayesian paradigm. Other aspects, like missing values in covariates within HD data and competing risk analysis, are also covered in this article.