31:T5ba,function addRegression(Plot) { Plot.regression = function ({ x, y, type, bandwidth, order, ...options }) { type = String(type).toLowerCase(); const regressor = type === "quad" ? reg.regressionQuad() : type === "poly" ? reg.regressionPoly() : type === "pow" ? reg.regressionPow() : type === "exp" ? reg.regressionExp() : type === "log" ? reg.regressionLog() : type === "loess" ? reg.regressionLoess() : reg.regressionLinear(); if (bandwidth && regressor.bandwidth) regressor.bandwidth(bandwidth); if (order && regressor.order) regressor.order(order); const z = options.z || options.stroke; // maybeZ return Plot.transform(options, function (data, facets) { const X = Plot.valueof(data, x); const Y = Plot.valueof(data, y); const Z = Plot.valueof(data, z); regressor.x((i) => X[i]).y((i) => Y[i]); const regFacets = []; const points = []; for (const facet of facets) { const regFacet = []; for (const I of Z ? d3.group(facet, (i) => Z[i]).values() : [facet]) { const reg = regressor(I); for (const d of reg) { const j = points.push(d) - 1; if (z) d[z] = Z[I[0]]; regFacet.push(j); } } regFacets.push(regFacet); } return { data: points, facets: regFacets }; }); }; return Plot; }32:[{"id":"30c90b75716db424723a99268675510fd5409405a879426c4f66299822bc899a731cfd714a74aa47d84623d9d7730df9a0e88b798e04f3e2bae3ef63714cc46c","href":"https://static.observableusercontent.com/files/30c90b75716db424723a99268675510fd5409405a879426c4f66299822bc899a731cfd714a74aa47d84623d9d7730df9a0e88b798e04f3e2bae3ef63714cc46c","name":"mtcars.csv","type":"text/csv","lastModified":1672739546944.849,"size":1699}] 2f:{"title":"Icke-linjär regression","cells":[{"id":0,"value":"md`# Icke-linjär regression`","pinned":false,"hidden":false,"mode":"ojs"},{"id":531,"value":"viewof param = type === \"LOESS\"\n ? Inputs.range([0, 1], { label: \"bandwidth (LOESS)\" })\n : type === \"Poly\"\n ? Inputs.range([1, 6], { label: \"poly order\", value: 3, step: 1 })\n : Object.assign(html`—`, { value: null })","pinned":false,"hidden":false,"mode":"ojs"},{"id":362,"value":"viewof type = Inputs.select([\"Linear\", \"Quad\", \"Poly\", \"Log\", \"Exp\", \"LOESS\"], {\n label: \"model type\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":364,"value":"plt = Plot.plot({\n grid: false,\n marks: [\n Plot.dot(mtcars, {\n x: \"hp\",\n y: \"mpg\",\n stroke: \"steelblue\",\n r: 1.5\n }),\n Plot.line(\n mtcars,\n Plot.regression({\n x: \"hp\",\n y: \"mpg\",\n stroke: \"orange\",\n strokeWidth: 2,\n type,\n bandwidth: param,\n order: param\n })\n ),\n Plot.line(\n penguins,\n Plot.regression({\n x: \"hp\",\n y: \"mpg\",\n type,\n bandwidth: param,\n order: param\n })\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":554,"value":"
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\n\n---\n## 🙈 Appendix 🙈\n\nHär följer bara kod och detaljer som du antagligen inte vill läsa.","pinned":false,"hidden":false,"mode":"md"},{"id":382,"value":"\n### Data","pinned":false,"hidden":false,"mode":"md"},{"id":512,"value":"mtcars = FileAttachment(\"mtcars.csv\").csv({typed: true});","pinned":false,"hidden":false,"mode":"ojs"},{"id":545,"value":"### Imports","pinned":false,"hidden":false,"mode":"md"},{"id":205,"value":"reg = require(\"d3-regression@1\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":441,"value":"Plot = addRegression(await require(\"@observablehq/plot@0.6\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":543,"value":"### Functions","pinned":false,"hidden":false,"mode":"md"},{"id":207,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W32","stdlib":"1","titling":"auto"}