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Showing 1 to 3 of 3 for “"degradation data analysis"”.

  1. Statistical Methods for Multivariate Functional Data Clustering, Recurrent Event Prediction, and Accelerated Degradation Data Analysis

    … project concentrates on the multivariate sensory data, the second project is related to the bivariate recurrent process, and the third project introduces thermal index (TI) estimation in accelerated destructive degradation test (ADDT) data, in which an R package is developed. All three projects …

    vt Repository record for Statistical Methods for Multivariate Functional Data Clustering, Recurrent Event Prediction, and Accelerated Degradation Data Analysis (opens in a new tab)

  2. Statistical Modeling and Predictions Based on Field Data and Dynamic Covariates

    Reliability analysis plays an important role in keeping manufacturers in a competitive position. It can be applied in many areas such as warranty predictions, maintenance scheduling, spare parts provisioning, and risk assessment. This dissertation focuses on statistical modeling and predictions …

    vt Repository record for Statistical Modeling and Predictions Based on Field Data and Dynamic Covariates (opens in a new tab)

  3. Functional Data Models for Raman Spectral Data and Degradation Analysis

    Functional data analysis (FDA) studies data in the form of measurements over a domain as whole entities. Our first focus is on the post-hoc analysis with pairwise and contrast comparisons of the popular functional ANOVA model comparing groups of functional data. Existing contrast tests assume …

    vt Repository record for Functional Data Models for Raman Spectral Data and Degradation Analysis (opens in a new tab)