{"spec_id":"acf-pacf","library":"muix","language":"javascript","code":"// anyplot.ai\n// acf-pacf: Autocorrelation and Partial Autocorrelation (ACF/PACF) Plot\n// Library: muix 7.29.1 | JavaScript 22.22.3\n// Quality: 84/100 | Created: 2026-06-10\n//# anyplot-orientation: landscape\n// anyplot.ai\n// acf-pacf: Autocorrelation and Partial Autocorrelation (ACF/PACF) Plot\n// Library: MUI X Charts | React | Node 22\n// License: @mui/x-charts — MIT (community). Pro/Premium are out of scope.\n// Quality: pending | Created: 2026-06-10\n\nimport { BarChart } from \"@mui/x-charts/BarChart\";\nimport { ChartsReferenceLine } from \"@mui/x-charts/ChartsReferenceLine\";\n\nconst t = window.ANYPLOT_TOKENS;\n\n// --- Deterministic LCG RNG (seed = 42) ---------------------------------------\nfunction lcgRng(seed) {\n let s = seed >>> 0;\n return () => {\n s = (Math.imul(s, 1664525) + 1013904223) >>> 0;\n return s / 4294967296;\n };\n}\n\nfunction randn(rng) {\n const u = Math.max(rng(), 1e-10);\n return Math.sqrt(-2 * Math.log(u)) * Math.cos(2 * Math.PI * rng());\n}\n\n// --- AR(2) time series: x_t = 0.65·x_{t-1} + 0.15·x_{t-2} + ε_t -----------\nconst rng = lcgRng(42);\nconst N = 300;\nconst ts = [0, randn(rng) * 0.5];\nfor (let i = 2; i < N; i++) {\n ts.push(0.65 * ts[i - 1] + 0.15 * ts[i - 2] + randn(rng));\n}\n\n// Centre and scale\nconst mu = ts.reduce((a, b) => a + b, 0) / N;\nconst cx = ts.map((x) => x - mu);\nconst c0 = cx.reduce((s, v) => s + v * v, 0) / N;\n\n// ACF at lag h\nfunction acfAt(h) {\n let s = 0;\n for (let i = h; i < N; i++) s += cx[i] * cx[i - h];\n return s / (N * c0);\n}\n\nconst MAX_LAG = 30;\nconst rho = Array.from({ length: MAX_LAG + 1 }, (_, k) => acfAt(k));\n\n// PACF via Durbin–Levinson recursion\nfunction computePACF(rhoArr, maxLag) {\n const pacf = [1, rhoArr[1]];\n let phi = [rhoArr[1]];\n for (let k = 2; k <= maxLag; k++) {\n let num = rhoArr[k];\n let den = 1;\n for (let j = 0; j < k - 1; j++) {\n num -= phi[j] * rhoArr[k - 1 - j];\n den -= phi[j] * rhoArr[j + 1];\n }\n const pkk = den !== 0 ? num / den : 0;\n pacf.push(pkk);\n const next = Array(k).fill(0);\n next[k - 1] = pkk;\n for (let j = 0; j < k - 1; j++) next[j] = phi[j] - pkk * phi[k - 2 - j];\n phi = next;\n }\n return pacf;\n}\n\nconst pacf = computePACF(rho, MAX_LAG);\n\n// 95% CI: ±1.96 / √N\nconst CI = 1.96 / Math.sqrt(N);\n\nconst round4 = (v) => Math.round(v * 10000) / 10000;\n\nconst acfLags = Array.from({ length: MAX_LAG + 1 }, (_, i) => String(i));\nconst pacfLags = Array.from({ length: MAX_LAG }, (_, i) => String(i + 1));\nconst acfData = rho.map(round4);\nconst pacfData = pacf.slice(1).map(round4);\n\n// --- Chart -------------------------------------------------------------------\nexport default function Chart() {\n const W = window.ANYPLOT_SIZE.width;\n const H = window.ANYPLOT_SIZE.height;\n\n const TITLE_H = 54;\n const PANEL_H = Math.floor((H - TITLE_H - 6) / 2);\n\n const barColor = t.palette[0]; // #009E73 — brand green\n\n const ciLineStyle = {\n stroke: t.inkSoft,\n strokeDasharray: \"7 4\",\n strokeWidth: 1.5,\n strokeOpacity: 0.85,\n };\n\n const zeroLineStyle = {\n stroke: t.inkSoft,\n strokeWidth: 0.7,\n strokeOpacity: 0.45,\n };\n\n const tickStyle = { fontSize: 12, fill: t.inkSoft };\n const labelStyle = { fontSize: 14, fill: t.ink };\n\n const axisLineSx = {\n \"& .MuiChartsAxis-line\": { stroke: t.grid },\n };\n\n const xAxisBase = {\n scaleType: \"band\" as const,\n categoryGapRatio: 0.62,\n tickLabelStyle: tickStyle,\n };\n\n const yAxisBase = {\n tickMinStep: 0.25,\n tickLabelStyle: tickStyle,\n labelStyle,\n };\n\n return (\n \n {/* Title */}\n \n AR(2) Process · acf-pacf · javascript · muix · anyplot.ai\n \n\n {/* ACF panel */}\n
\n \n \n \n \n \n
\n\n {/* PACF panel */}\n
\n \n \n \n \n \n
\n \n );\n}\n"}