[go: up one dir, main page]

Wang et al., 2011 - Google Patents

Empirical likelihood for quantile regression models with longitudinal data

Wang et al., 2011

Document ID
4693841908635392820
Author
Wang H
Zhu Z
Publication year
Publication venue
Journal of statistical planning and inference

External Links

Snippet

We develop two empirical likelihood-based inference procedures for longitudinal data under the framework of quantile regression. The proposed methods avoid estimating the unknown error density function and the intra-subject correlation involved in the asymptotic covariance …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/18Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for functional genomics or proteomics, e.g. genotype-phenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, protein-protein interactions or protein-nucleic acid interactions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/70Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds
    • G06F19/708Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds for data visualisation, e.g. molecular structure representations, graphics generation, display of maps or networks or other visual representations
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/16Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for molecular structure, e.g. structure alignment, structural or functional relations, protein folding, domain topologies, drug targeting using structure data, involving two-dimensional or three-dimensional structures
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/48Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/70Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds
    • G06F19/706Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds for drug design with the emphasis on a therapeutic agent, e.g. ligand-biological target interactions, pharmacophore generation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F11/00Error detection; Error correction; Monitoring

Similar Documents

Publication Publication Date Title
Wang et al. Empirical likelihood for quantile regression models with longitudinal data
Elashoff et al. An approach to joint analysis of longitudinal measurements and competing risks failure time data
Wang et al. Confounder adjustment in multiple hypothesis testing
Weber et al. Applying meta-analytic-predictive priors with the R Bayesian evidence synthesis tools
Chiou et al. Fitting accelerated failure time models in routine survival analysis with R package aftgee
Pan et al. Regression analysis of additive hazards model with latent variables
Sun et al. Semiparametric time‐varying coefficients regression model for longitudinal data
Zhang et al. Checking the adequacy for a distortion errors-in-variables parametric regression model
Ke et al. Bayesian meta-analytic SEM: A one-stage approach to modeling between-studies heterogeneity in structural parameters
Torabi Likelihood inference in generalized linear mixed measurement error models
He et al. Additive mean residual life model with latent variables under right censoring
CN106770155B (en) A kind of substance content analysis method
Zhao et al. Covariate measurement error correction methods in mediation analysis with failure time data
Lunn et al. Markov chain Monte Carlo techniques for studying interoccasion and intersubject variability: application to pharmacokinetic data
Habeck et al. Bayesian estimation of Karplus parameters and torsion angles from three-bond scalar couplings constants
Pan et al. Joint analysis of mixed types of outcomes with latent variables
Maceachern et al. Importance link function estimation for Markov chain Monte Carlo methods
Li et al. Survival analysis with heterogeneous covariate measurement error
Gregorich et al. Prediction Modeling With Many Correlated and Zero‐Inflated Predictors: Assessing the Nonnegative Garrote Approach
Chen et al. Principal component analyses in anthropological genetics
Rodríguez-Girondo et al. Sequential double cross-validation for assessment of added predictive ability in high-dimensional omic applications
Koner et al. Power and Sample Size Calculation of Two‐Sample Projection‐Based Testing for Sparsely Observed Functional Data
Ma et al. Quantile regression modeling of latent trajectory features with longitudinal data
Pantazis et al. Performance of parametric survival models under non-random interval censoring: A simulation study
Ferede et al. A mixed-effects joint model with skew-t distribution for longitudinal and time-to-event data: A Bayesian approach