Density Estimation for Statistics and Data Analysis

Silverman, B. W. (1986). Density Estimation for Statistics and Data Analysis. Chapman & Hall.

Type

Book

Intellectual base

Review or monograph

Year

1986

DOI

10.1201/9781315140919

ISBN

9781315140919

Link

https://doi.org/10.1201/9781315140919

Cited from

mathematics

Cited by

3 citations across 3 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Discretization-Induced Artifact
  • Statistics: histogram-binning artefacts — gaps, modes, and bimodality that shift with bin width and anchor and vanish under kernel-density estimation.

    This sourceHistogram modes and gaps depend on bin width and anchor and dissolve under kernel-density estimation; the invariance test against binning choices.

• Modifiable Areal Unit Problem
  • In histograms and exploratory analysis, the same continuous data displays as unimodal or bimodal depending on bin choice, with kernel-density bandwidth as the continuous analog.

    This sourceHistogram appearance (unimodal vs bimodal) depends on bin choice; kernel-density bandwidth is the continuous analog of bin width.

Domain-specific

• Violin Plot
  • The violin maps \(x\) to the value axis and \(\widehat f_h(x)\) to half-width.

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