Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Mangalam Kumaraswamy Sridhar

ABSTRACT:

SUBMITTER: Brankin E

PROVIDER: S-EPMC1557927 | biostudies-literature | 2006 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Inference for partially observed competing risks model for Kumaraswamy distribution under generalized progressive hybrid censoring.

Project description:In this paper, inference for a competing risks model is studied when latent failure times follow Kumaraswamy distribution and causes of failure are partially observed. Under generalized progressive hybrid censoring, existence and uniqueness of maximum likelihood estimators of model parameters are established. The confidence intervals are obtained by using asymptotic distribution theory. We further compute Bayes estimators along with credible intervals. In addition, inference is also discussed when there is order restricted shape parameters. The performance of all estimates is investigated using Monte-Carlo simulations. Finally, analysis of a real data set is presented for illustration purposes.

| S-EPMC9225323 | biostudies-literature

The principle of maximum entropy and the probability-weighted moments for estimating the parameters of the Kumaraswamy distribution.

Project description:Since Shannon's formulation of the entropy theory in 1940 and Jaynes' discovery of the principle of maximum entropy (POME) in 1950, entropy applications have proliferated across a wide range of different research areas including hydrological and environmental sciences. In addition to POME, the method of probability-weighted moments (PWM), was introduced and recommended as an alternative to classical moments. The PWM is thought to be less impacted by sampling variability and be more efficient at obtaining robust parameter estimates. To enhance the PWM, self-determined probability-weighted moments was introduced by (Haktanir 1997). In this article, we estimate the parameters of Kumaraswamy distribution using the previously mentioned methods. These methods are compared to two older methods, the maximum likelihood and the conventional method of moments techniques using Monte Carlo simulations. A numerical example based on real data is presented to illustrate the implementation of the proposed procedures.

| S-EPMC9154196 | biostudies-literature

Kumaraswamy inverse Gompertz distribution: Properties and engineering applications to complete, type-II right censored and upper record data.

Project description:This article proposes and studies a new three-parameter generalized model of the inverse Gompertz distribution, in the so-called Kumaraswamy inverse Gompertz distribution. The main advantage of the new model is that it has "an upside down bathtub-shaped curve hazard rate function" depending upon the shape parameters. Several of its statistical and mathematical properties including quantiles, median, mode, moments, probability weighted moment, entropy function, skewness and kurtosis are derived. Moreover, the reliability and hazard rate functions, mean time to failure, mean residual and inactive lifetimes are also concluded. The maximum likelihood approach is done here to estimate the new model parameters. A simulation study is conducted to examine the performance of the estimators of this model. Finally, the usefulness of the proposed distribution is illustrated with different engineering applications to complete, type-II right censored, and upper record data and it is found that this model is more flexible when it is compared to well-known models in the statistical literature.

| S-EPMC7714165 | biostudies-literature

Statistical inference for a constant-stress partially accelerated life tests based on progressively hybrid censored samples from inverted Kumaraswamy distribution.

Project description:In this article, we investigate the problem of point and interval estimations under constant-stress partially accelerated life tests. The lifetime of items under use condition is assumed to follow the two-parameter inverted Kumaraswamy distribution. Based on Type-I progressively hybrid censored samples, the maximum likelihood and Bayesian methods are applied to estimate the model parameters as well as the acceleration factor. Under linear exponential, general entropy and squared error loss functions, Bayesian method outcomes are obtained. In addition, interval estimation is achieved by finding approximately confidence intervals for the parameters, as well as credible intervals. To investigate the accuracy of the obtained estimates and to compare the performance of confidence intervals, a Monte Carlo simulation is developed. Finally, a set of real data is analyzed to demonstrate the estimation procedures.

| S-EPMC9342795 | biostudies-literature

LINCS MCF 10A Common Project: Highly-multiplexed imaging by Cyclic Immunofluorescence (CycIF) of protein levels and protein phosphorylation states in the MCF 10A breast cell line treated with 8 small molecule perturbagens. Dataset 6 of 6: Nuclear fluorescent intensity measurements at 72 hr.

Project description: Not available

2017-05-12 | LDS-1407 | LINCS

FoxO3a nuclear-cytoplasmic pulsing dynamics in a mammary epithelial cell line following growth-factor treatment with varying ERK/AKT activation loads. Dataset 3 of 3: mean reporter pulsing metrics.

Project description: Not available

2017-05-02 | LDS-1384 | LINCS

MEMA PC3 Staining Set 2

Project description:Cell cycle and nuclear state imaging readouts for PC3 cells treated with ligand and ECMp combinations to explore the role of microenvironmental signals in cancer growth.

2016-03-09 | LDS-1315 | LINCS

GCP aggregated data - Chemical perturbations

Project description:Global chromatin epigentic profiles of human cancer and NPC cell lines treated with neurodevelopmental compounds, epigenetic compounds and kinase inhibitors.

2020-04-13 | LDS-41235 | LINCS

LINCS Pilot Phase Joint Project: Sensitivity measures of six breast cancer cell lines to a library of small molecule kinase inhibitors (single drug treatments). Dataset 5 of 15: Mean cell count and mean growth rate across biological replicate 2.

Project description:-

2017-03-14 | LDS-1230 | LINCS

Sensitivity measures of MDA-MB-231 and HME-1 cell lines to LINCS Pilot Phase TransCenter Project kinase inhibitors

Project description:-

2015-07-01 | LDS-1206 | LINCS