Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Climate-based forecasting from national Culex mosquito surveillance to support West Nile and Usutu virus preparedness in England and Wales.

BMC public health·2026
Same author

Evaluation of the Entomological Adaptive Surveillance Framework for malaria vector monitoring: a comparative field trial with routine surveillance in Ghana and Mozambique.

BMJ public health·2026
Same author

Identification of malaria hotspots in southwestern Benin through spatial joint modelling of malaria incidence and vector abundance.

Malaria journal·2026
Same author

Behavioral patterns in latrine use and handwashing in rural western Kenya: Age, time of day, and the role of perceived safety.

PloS one·2026
Same author

The anatomical knowledge of Namibian school children.

Anatomical sciences education·2025
Same author

Structural features of outdoor latrines influence the abundance of Anopheles gambiae s.l. and Culex quinquefasciatus in a village in Kisumu County, western Kenya.

Parasites & vectors·2025
Same journal

Schistosomal circulating anodic antigen dynamics pre- and post-treatment in preschool aged children from the PIP trial in Uganda.

Parasitology·2026
Same journal

Rapid diagnostic assay distinguishing the snail vectors <i>Bulinus globosus</i> and <i>Bulinus nasutus</i> for urogenital schistosomiasis transmission risk mapping in East Africa.

Parasitology·2026
Same journal

Identification and coregulation pattern analysis of long noncoding RNAs in the mouse macrophages after Leishmania donovani infection.

Parasitology·2026
Same journal

Persistent intestinal schistosomiasis and progressive liver fibrosis in semi-captive chimpanzees: A 12-year epidemiological follow-up in Ngamba Island Chimpanzee Sanctuary, Lake Victoria, Uganda.

Parasitology·2026
Same journal

Parasites of a keystone megaherbivore: insights into trematode life cycles and biological invasions in the Greater Kruger ecosystem.

Parasitology·2026
Same journal

Integrative description of <i>Udonella umgibeli</i> n. sp. (Monopisthocotylea: Udonellidae) as an epibiont of <i>Caligus tetrodontis</i> Barnard, 1948, off the coast of South Africa.

Parasitology·2026
See all related articles

Related Experiment Video

Updated: May 17, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

Statistical models for spatially explicit biological data.

David J Rogers1, Luigi Sedda

  • 1University of Oxford, Department of Zoology, Oxford OX1 3PS, UK. david.rogers@zoo.ox.ac.uk

Parasitology
|October 23, 2012
PubMed
Summary
This summary is machine-generated.

Geostatistical methods like kriging improve species distribution predictions by incorporating spatial data and estimating prediction errors. These techniques offer a more robust alternative to aspatial models for ecological forecasting.

More Related Videos

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

Published on: October 11, 2016

Related Experiment Videos

Last Updated: May 17, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

Published on: October 11, 2016

Area of Science:

  • Ecology
  • Biogeography
  • Spatial Statistics

Background:

  • Most species distribution models are aspatial, neglecting spatial context and neighboring areas.
  • Geostatistical techniques offer a spatial approach to species distribution prediction.

Purpose of the Study:

  • To introduce and encourage the use of geostatistical techniques (kriging and cokriging) in ecological studies.
  • To demonstrate the application of geostatistical methods using bluetongue outbreak data.

Main Methods:

  • Application of kriging and cokriging for spatial prediction.
  • Analysis of prediction errors provided by geostatistical methods.
  • Interpretation of weights in geostatistical calculations.

Main Results:

  • Geostatistical techniques provide estimates of prediction errors, unlike deterministic spatial methods.
  • Covarying environmental data can enhance predictions if sampled more frequently than species data.
  • Cokriging cannot determine the biological significance of environmental data.

Conclusions:

  • Geostatistical methods offer valuable spatial prediction capabilities for species distributions.
  • Understanding geostatistical weights is crucial for accurate interpretation.
  • Limitations exist in cokriging's ability to assess biological significance of environmental covariates.