# Questions tagged [rms]

RMS stands for 'root-mean-square' is a measure of the typical size of a varying quantity. It occurs in the n-denominator form of standard deviation (the RMS deviation from the mean)

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### Normalization of log-returns or normalization of cumulative log-returns

This questions seeks for discussion to find theoretical support for normalizing cumulative log-returns vs normalizing log-returns By "normalizing" (also known as standarizing) I mean it in ...
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### Cox model with ridge term: how to choose value of theta?

The coxph() function in R package "survival" is used to fit the Cox proportional hazards model. This function allows a ridge() term in the formula to penalise selected terms, which requires ...
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### Root Mean Square Error of the addition of two measurements whose RMS Error is known

I am working on a measurement system which tries to measure the distance between two values i.e $\Delta F=F_1-F_2$. Where $F_1, F_2$ are the values I actually measure. I have set up a Monte Carlo ...
1 vote
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### Can I say that the relative root mean squared error is the averaged percentage error?

RMSE is an error metric in which the mean of the data minimizes its loss function: $\text{RMSE} = \sqrt{\frac{\sum_{t=1}^{n}(y_t - \hat{y_t})^2}{n}}$ But it gives ...
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### What is the uncertainty of Leave-one-out-cross-validation method?

I have used the LOOCV to validate my model. As we know, the LOOCV method is a special case of cross-validation where the number of folds equals the number of instances in the data set. Thus, the ...
1 vote
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### Confirming cubic spline was done on imputed datasets (imputed by mice Package) and the estimate is the pooled based on Rubin's rule

I am performing restricted cubic spline (Cox proportional hazard ratio) after imputing 10 datasets using mice package. My variables as follow: Outcome: DM Exposure: BMI time to events: time Covariates:...