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doc/pub/week36/html/._week36-bs022.html

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@@ -346,7 +346,7 @@ <h2 id="more-interpretations" class="anchor">More interpretations </h2>
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<p>In this case the standard OLS results in </p>
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$$
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\boldsymbol{\theta}^{\mathrm{OLS}} = \boldsymbol{X}^T\boldsymbol{y}=\sum_{i=0}^{n-1}\boldsymbol{u}_i\boldsymbol{u}_i^T\boldsymbol{y},
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\boldsymbol{\theta}^{\mathrm{OLS}} = \boldsymbol{X}^T\boldsymbol{y},
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$$
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<p>and</p>
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infinity.
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</p>
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<p>We will come back to more interpreations after we have gone through some of the statistical analysis part. </p>
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<p>We will come back to more interpretions after we have gone through some of the statistical analysis part. </p>
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<p>For more discussions of Ridge and Lasso regression, <a href="https://arxiv.org/abs/1509.09169" target="_self">Wessel van Wieringen's</a> article is highly recommended.
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Similarly, <a href="https://arxiv.org/abs/1803.08823" target="_self">Mehta et al's article</a> is also recommended.

doc/pub/week36/html/week36-reveal.html

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<p>In this case the standard OLS results in </p>
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<p>&nbsp;<br>
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$$
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\boldsymbol{\theta}^{\mathrm{OLS}} = \boldsymbol{X}^T\boldsymbol{y}=\sum_{i=0}^{n-1}\boldsymbol{u}_i\boldsymbol{u}_i^T\boldsymbol{y},
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\boldsymbol{\theta}^{\mathrm{OLS}} = \boldsymbol{X}^T\boldsymbol{y},
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$$
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<p>&nbsp;<br>
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infinity.
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</p>
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<p>We will come back to more interpreations after we have gone through some of the statistical analysis part. </p>
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<p>We will come back to more interpretions after we have gone through some of the statistical analysis part. </p>
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<p>For more discussions of Ridge and Lasso regression, <a href="https://arxiv.org/abs/1509.09169" target="_blank">Wessel van Wieringen's</a> article is highly recommended.
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Similarly, <a href="https://arxiv.org/abs/1803.08823" target="_blank">Mehta et al's article</a> is also recommended.

doc/pub/week36/html/week36-solarized.html

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<p>In this case the standard OLS results in </p>
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$$
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\boldsymbol{\theta}^{\mathrm{OLS}} = \boldsymbol{X}^T\boldsymbol{y}=\sum_{i=0}^{n-1}\boldsymbol{u}_i\boldsymbol{u}_i^T\boldsymbol{y},
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\boldsymbol{\theta}^{\mathrm{OLS}} = \boldsymbol{X}^T\boldsymbol{y},
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$$
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<p>and</p>
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infinity.
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</p>
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<p>We will come back to more interpreations after we have gone through some of the statistical analysis part. </p>
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<p>We will come back to more interpretions after we have gone through some of the statistical analysis part. </p>
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<p>For more discussions of Ridge and Lasso regression, <a href="https://arxiv.org/abs/1509.09169" target="_blank">Wessel van Wieringen's</a> article is highly recommended.
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Similarly, <a href="https://arxiv.org/abs/1803.08823" target="_blank">Mehta et al's article</a> is also recommended.

doc/pub/week36/html/week36.html

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<p>In this case the standard OLS results in </p>
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$$
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\boldsymbol{\theta}^{\mathrm{OLS}} = \boldsymbol{X}^T\boldsymbol{y}=\sum_{i=0}^{n-1}\boldsymbol{u}_i\boldsymbol{u}_i^T\boldsymbol{y},
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\boldsymbol{\theta}^{\mathrm{OLS}} = \boldsymbol{X}^T\boldsymbol{y},
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$$
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<p>and</p>
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infinity.
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</p>
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<p>We will come back to more interpreations after we have gone through some of the statistical analysis part. </p>
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<p>We will come back to more interpretions after we have gone through some of the statistical analysis part. </p>
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<p>For more discussions of Ridge and Lasso regression, <a href="https://arxiv.org/abs/1509.09169" target="_blank">Wessel van Wieringen's</a> article is highly recommended.
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Similarly, <a href="https://arxiv.org/abs/1803.08823" target="_blank">Mehta et al's article</a> is also recommended.
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