(Q46058026)

19 December 2017

title

A nonparametric subject-specific population method for deconvolution: II. External validation (English)

1 reference

19 December 2017

1 reference

K E Fattinger

1

1 reference

19 December 2017

D Verotta

series ordinal

2

1 reference

19 December 2017

publication date

1 December 1995

1 reference

19 December 2017

Journal of Pharmacokinetics and Pharmacodynamics

published in

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19 December 2017

volume

23

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19 December 2017

issue

6

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19 December 2017

page(s)

611-634

1 reference

19 December 2017

https://scigraph.springernature.com/pub.10.1007/bf02353464

exact match

0 references

cites work

Comments on two recent deconvolution methods

1 reference

https://api.crossref.org/works/10.1007%2FBF02353464

A new look at the statistical model identification

21 January 2018

1 reference

https://api.crossref.org/works/10.1007%2FBF02353464

Spline Models for Observational Data

21 January 2018

1 reference

https://api.crossref.org/works/10.1007%2FBF02353464

Population pharmacokinetic data and parameter estimation based on their first two statistical moments

21 January 2018

1 reference

https://api.crossref.org/works/10.1007%2FBF02353464

Non-linear models for the analysis of longitudinal data

21 January 2018

1 reference

https://api.crossref.org/works/10.1007%2FBF02353464

A new method to explore the distribution of interindividual random effects in non-linear mixed effects models

21 January 2018

1 reference

PubMed

https://pubmed.ncbi.nlm.nih.gov/8733949

inferred from PubMed ID database lookup

12 December 2020

based on heuristic

A nonparametric subject-specific population method for deconvolution: I. Description, internal validation, and real data examples

1 reference

PubMed

https://pubmed.ncbi.nlm.nih.gov/8733949

inferred from PubMed ID database lookup

12 December 2020

based on heuristic

Identifiers

DOI

10.1007/BF02353464

1 reference

19 December 2017

1 reference

19 December 2017