The avatar for @mattiasvillani
Mattias Villani
Professor of Statistics at Stockholm University
Public
Edited
Feb 4, 2024
Fork of Maximum likelihood - Poisson regression
1
STM
The exponential functionThe logarithm functionThe derivativeA function and its derivativesThe Riemann integralThe Taylor approximationBernoulli distributionBinomial distributionPoisson distributionGeometric distributionNegative binomial distributionUniform distributionTriangular distributionNormal (Gaussian) distributionExponential distributionGamma distributionChi2-distributionWeibull distributionBeta distributionStudent-t distribution (three-parameter)Chebyshev's inequalityMaximum likelihood - Poisson regressionCentral limit theoremLaw of Large NumbersSecond derivative measures the curvature of a functionConfidence interval for a meanSampling distribution and likelihood function - Bernoulli modelMaximum likelihood - Bernoulli data
Maximum likelihood for iid Poisson data
Multivariate normal distributionFunction optimization
Also listed in…
Basic Statistics
SDA3
Bayesian Learning
SDA1
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import {toc} from "@mbostock/toc"
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import {addColumn} from "@observablehq/excel-add-columns"
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optimjs = require('optimization-js@1.5.0/dist/optimization.js')
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reserve_threshold = 0.575 // threshold to obtain the auction with lowest reserve prices
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yaxislabel = {if (settings[2]){return "log-likelihood"}else{return "average probability for a single observation"}}
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data_high = ebaydata.filter(d => d.ReservePriceFrac > reserve_threshold)
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y = Array.from(d3.map(data, d => d.NBidders))
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y_high = Array.from(d3.map(data_high, d => d.NBidders))
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mle = d3.mean(y)
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mle_high = d3.mean(y_high)
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