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Ratings and Reviews 0 Ratings
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What is GUMsim?
Measurements inevitably experience variations from their true values, a scenario referred to as measurement uncertainty, which is particularly relevant when evaluating or calibrating measurement instruments or methods. Accurately quantifying this uncertainty is crucial for maintaining quality control. GUMsim®, compliant with the most recent Guide to the Expression of Uncertainty in Measurement (GUM) and its supplement 1, employs advanced computational algorithms that support a more efficient assessment of measurement uncertainty in accordance with ISO/IEC 17025 standards. The assessment of measurement uncertainty relies on a mathematical framework and statistical evaluation of all factors that affect measurement results. To simplify this procedure, GUMsim offers an intuitive input interface suitable for various measurement models. Furthermore, it includes multiple pre-defined application models, which serve as templates designed to aid users in carrying out specific evaluations, facilitating the initiation of measurement uncertainty assessments. This aspect not only improves the overall user experience but also promotes uniformity in measurement practices across diverse applications, ultimately reinforcing the reliability of measurement results. As a result, users can approach their uncertainty evaluations with greater confidence and efficiency.
What is ArcGIS Geostatistical Analyst?
Relying exclusively on real-world observations to predict and model spatial phenomena can often be impractical or unfeasible. With the ArcGIS Geostatistical Analyst, users can develop optimal surfaces from sample data while evaluating predictions to improve decision-making processes. This powerful tool is especially advantageous for examining atmospheric conditions, investigating petroleum and mining prospects, performing environmental assessments, implementing precision agriculture, and analyzing fish and wildlife populations. The extension is equipped with a diverse array of interactive tools that facilitate a visual inspection of the data before moving on to deeper analysis. In situations where the data may be incomplete or susceptible to inaccuracies, ArcGIS Geostatistical Analyst provides a probabilistic framework to effectively measure uncertainties. Users can create multiple surface scenarios to perform risk analyses, as geostatistical simulation allows for the development of various surfaces that accurately reflect real-world phenomena and offer a spectrum of potential values. This capability not only contributes to a better understanding of uncertainties but also significantly bolsters the overall reliability of the analyses conducted. Furthermore, the flexibility of the tool ensures that users can adapt their approach based on specific project needs, leading to more informed and strategic outcomes.
Integrations Supported
ArcGIS Pro
API Availability
Has API
API Availability
Has API
Pricing Information
€870 one-time payment
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
QuoData
Company Location
Germany
Company Website
www.quodata.de/gumsim
Company Facts
Organization Name
Esri
Date Founded
1969
Company Location
United States
Company Website
www.esri.com/en-us/arcgis/products/geostatistical-analyst/overview
Categories and Features
Statistical Analysis
Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization