first-order-model-fitting
CommunityExtract K and tau from step-response data.
Data & Analytics#engineering#data-analysis#parameter-estimation#curve-fitting#first-order#system-modeling#step-response
AuthorKaiserWhoLearns
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill enables rapid estimation of first-order dynamics by extracting gain K and time constant tau from a step-response dataset, turning raw measurements into quantified system parameters.
Core Features & Use Cases
- Parameter estimation: fit a first-order model to step-response data to obtain K, tau, and ambient baseline.
- Broad applicability: suitable for thermal, electrical, and mechanical systems with step inputs and measurable outputs.
- Use Case: determine how a heater's input power translates to temperature rise by fitting experimental data to the model.
Quick Start
Provide a time-series of step-response data and run the first-order model fit to obtain K and tau.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: first-order-model-fitting Download link: https://github.com/KaiserWhoLearns/skillsbench/archive/main.zip#first-order-model-fitting Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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