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API · /regression-api

Linear Regression API

healthy 4,651 Subscribers

Linear least-squares regression as an API, computed locally and deterministically. The linear endpoint fits the best straight line y = a + b·x through a set of x/y data points by ordinary least squares, returning the slope b = Σ((x−x̄)(y−ȳ))/Σ(x−x̄)², the intercept a = ȳ − b·x̄, the ready-to-use equation, the Pearson correlation r and the coefficient of determination R² (the fraction of variance the line explains), and the residual and slope standard errors — the points (1,2),(2,4),(3,5),(4,4),(5,5) fit to y = 2.2 + 0.6·x with R² = 0.6, and a perfectly linear set returns R² = 1. Pass a predict_x and it also extrapolates the fitted value at that point. The predict endpoint evaluates y = intercept + slope·x for a known line. The x and y lists may be given as comma-separated values (x=1,2,3&y=2,4,5) or as JSON arrays in a POST body and must be equal length. Everything is computed locally and deterministically, so it is instant and private. Ideal for data-science, analytics, BI, forecasting, machine-learning-preprocessing and statistics-education app developers, trend-line and best-fit tools, and dashboards. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 2 endpoints. This is the regression line; for the Pearson correlation alone or descriptive statistics use a statistics API and for probability distributions a probability API.

#regression #least-squares #trend-line #data-science #analytics #developer-tools
api.oanor.com/regression-api
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Machine-readable spec so AI agents can integrate this API.

/api/regression-api/openapi.json
/api/regression-api/llms.txt

Discovery: GET /api/index.json lists every API.

API health

healthy
Uptime
100.00%
Server probes · 24h
Avg latency
88 ms
Server probes · 24h
Subscribers
4,651
active
Total calls
15
last 7 days
status Full status page → · 15 probes/24h

Pricing

Pick a tier — billed monthly, cancel anytime.

Free

Free

  • 5,600 calls / month
  • 2 requests / second
  • Hard cap (429 above quota, no overage)
  • 5,600 calls/month
  • 2 req/sec
  • Slope + intercept + R² + prediction
  • No credit card
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Starter

€5.70 /month

  • 56,000 calls / month
  • 6 requests / second
  • Hard cap (429 above quota, no overage)
  • 56,000 calls/month
  • 6 req/sec
  • Standard errors, array or comma input
  • Email support
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Pro

€16.80 /month

  • 260,000 calls / month
  • 15 requests / second
  • Hard cap (429 above quota, no overage)
  • 260,000 calls/month
  • 15 req/sec
  • Analytics & forecasting pipelines
  • Priority support
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Mega

€53.00 /month

  • 1,480,000 calls / month
  • 40 requests / second
  • Hard cap (429 above quota, no overage)
  • 1,480,000 calls/month
  • 40 req/sec
  • Platform scale
  • Dedicated SLA
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Related APIs

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Statistics Calculator API

Descriptive-statistics maths as an API, computed locally and deterministically. The descriptive endpoint summarises a list of numbers — the count, sum, mean, median, mode, minimum, maximum and range, the population and sample variance and standard deviation, and the quartiles Q1/Q2/Q3 with the interquartile range by Tukey's method. The correlation endpoint computes the Pearson correlation coefficient r between two equal-length series — from −1 (perfect inverse) through 0 (none) to +1 (perfect direct) — along with R² and the covariance. The regression endpoint fits a least-squares line y = a + b·x, returning the slope, intercept and R², the equation, and an optional prediction for a given x. Data is accepted as a JSON array or a comma-separated list. Everything is computed locally and deterministically, so it is instant and private. Ideal for data-analysis, dashboard, research and education app developers, reporting and BI tools, and spreadsheet replacements. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is descriptive statistics; for probability distributions and combinatorics use a probability API.

api.oanor.com/statistics-api

Statistics API

Run statistics on a list of numbers without a spreadsheet or a stats package. The describe endpoint returns a full summary of a dataset — count, sum, min, max, range, mean, median, mode, the first and third quartiles and interquartile range, population and sample variance and standard deviation, coefficient of variation, geometric and harmonic means, skewness and kurtosis. Get any percentile of a dataset, the Pearson correlation coefficient (and r²) between two equal-length series, and a simple linear regression (slope, intercept, r² and the line equation). Input is a raw array of numbers (JSON or a comma-separated list) — no CSV, no headers. Perfect for analytics, A/B test summaries, sensor and metrics data, dashboards and quick exploratory analysis. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 5 endpoints. Distinct from the mathjs expression engine and from CSV per-column summaries.

api.oanor.com/stats-api

Classifier Metrics API

Classifier-evaluation maths as an API, computed locally and deterministically. The confusion endpoint turns the four cells of a binary confusion matrix — true and false positives and negatives — into the full metric suite: accuracy, precision, recall (sensitivity), specificity, the F1 score, the Matthews correlation coefficient (robust to class imbalance), balanced accuracy, negative predictive value, the false-positive and false-negative rates and the prevalence. The diagnostic endpoint applies Bayes' theorem to a medical or screening test: from its sensitivity, specificity and the prevalence (pre-test probability) it gives the positive and negative predictive values, the positive and negative likelihood ratios and the diagnostic odds ratio. The fbeta endpoint computes the Fβ score from precision and recall (or from the raw counts) for any β — β = 1 is F1, larger β weights recall, smaller β weights precision. Metrics whose denominator is zero are returned as null rather than erroring. Everything is computed locally and deterministically, so it is instant and private. Ideal for machine-learning, data-science, medical-testing and analytics app developers, model-evaluation and screening tools, and statistics education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is classifier evaluation; for descriptive statistics and regression use a statistics API and for hypothesis tests an inference API.

api.oanor.com/classifier-api

CRAN API

The R package ecosystem — CRAN, the Comprehensive R Archive Network — as an API. Look up any R package for its title, description, version, license, maintainer and author, homepage and bug-tracker links, and its full dependency tree (depends, imports, suggests, linkingTo); read a package's complete release history with publication dates; search the entire CRAN registry by keyword; and get download statistics (last day, week or month, with an optional daily series) straight from the official CRAN download logs. Covers the ~22,000 packages on CRAN, from ggplot2, dplyr and data.table to jsonlite, shiny and the wider tidyverse. Live from the official R-community services (crandb, search.r-pkg.org, cranlogs). Ideal for package dashboards, dependency and supply-chain tooling, data-science developer portals and R ecosystem analytics. Open data from CRAN.

api.oanor.com/cran-api

Frequently asked questions

Quick answers about pricing, quotas, and integration.

How do I get an API key for Linear Regression API?
Sign up for free at oanor.com, generate an API key from the developer dashboard, and call Linear Regression API with the x-oanor-key header. No credit card needed for the free tier.
What's the rate limit for Linear Regression API?
Free tier allows 1 request per second. Paid plans scale up to 50 requests per second on the Mega tier. Hard limits return HTTP 429 above the quota — no surprise overage charges.
How much does Linear Regression API cost?
Linear Regression API has a free tier with 100 calls / month. Paid plans start at €5.70 / month with higher quotas and faster rate limits.
Can I cancel my subscription anytime?
Yes. Plans are billed monthly and you can cancel anytime from your billing dashboard. No long-term contracts and no cancellation fee.
Is Linear Regression API GDPR-compliant?
All requests to Linear Regression API go through our EU-based gateway. Your upstream API key never leaves our server and no personal data is shared with the upstream provider beyond the request you send.

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Code snippets

Sign up to get an API key, then call any path under your slug.

curl https://api.oanor.com/regression-api/SOME_PATH \
  -H "x-oanor-key: oanor_test_..."
const res = await fetch("https://api.oanor.com/regression-api/SOME_PATH", {
  headers: { "x-oanor-key": "oanor_test_..." }
});
const data = await res.json();
$ch = curl_init("https://api.oanor.com/regression-api/SOME_PATH");
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_HTTPHEADER, ["x-oanor-key: oanor_test_..."]);
$response = curl_exec($ch);
import requests
r = requests.get(
    "https://api.oanor.com/regression-api/SOME_PATH",
    headers={"x-oanor-key": "oanor_test_..."},
)
print(r.json())

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