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Use this tag for any *on-topic* question that (a) involves `R` either as a critical part of the question or expected answer, & (b) is not *just* about how to use `R`.

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Machine learning with univariate time series

goals there are different from (classical) time series problems and there are well established application focused solutions not based on generic or vanilla methods as found in ML libraries (Python or R
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3 votes
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High Correlation Between Residuals and Dependent Variable

Correlation of residuals with response is not a surprise as the response is modeled as a regression part plus residuals. Given that the model doesn't fully explain the data, the remaining 'explanation …
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1 vote

Detecting changes in time series (R example)

Here is an R-snippet producing the self-explanatory graphs below. outl = rep( NA, length(dat.change)) detr = c( 0, diff( dat.change)) ix = abs(detr) > 2*IQR( detr) outl[ix] = dat.change[ix] plot( dat.change …
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2 votes

One-to-one correspondence between penalty parameters of equivalent formulations of penalised...

Assume that the solution of your problem $(1)$ is $\beta_\lambda^*$, where index $\lambda$ indicates dependence on a particular value of $\lambda$. The second problem is solved using Langrange multip …
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