P281424/AMR
1
0
Fork 0
mirror of https://github.com/msberends/AMR.git synced 2026-06-29 08:56:20 +02:00
Code Releases Activity

Built site for AMR@3.0.1.9077: f7d3533

Browse Source
This commit is contained in:
github-actions
2026-06-26 19:49:26 +00:00
parent 108afaca6f
commit 169659837d
93 changed files with 368 additions and 239 deletions
Download Patch File Download Diff File Expand all files Collapse all files

7
reference/ggplot_pca.html
View File

@@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9076</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">3.0.1.9077</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -113,8 +113,9 @@
<dt id="arg-pc-biplot">pc.biplot<a class="anchor" aria-label="anchor" href="#arg-pc-biplot"></a></dt>
<dd><p>If true, use what Gabriel (1971) refers to as a "principal component
biplot", with <code>lambda = 1</code> and observations scaled up by sqrt(n) and
<dd><p>If true, use what <cite></cite><a href="#reference+biplot.princomp.Rd+R+3AGabriel+3A1971" class="citation">Gabriel (1971)</a> refers to as a
“principal component biplot”,
with <code>lambda = 1</code> and observations scaled up by sqrt(n) and
variables scaled down by sqrt(n). Then inner products between
variables approximate covariances and distances between observations
approximate Mahalanobis distance.</p></dd>