Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

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)

RMS stands for 'root-mean-square' is a measure of the size of a varying quantity. It is a kind of power-mean, generalized mean, and Fréchet mean.

It occurs in the n-denominator form of standard deviation - the RMS deviation from the mean.

In statistics, the term most commonly occurs in the phrase "root mean square error" (with the common acronym "RMSE")

Please do not use this tag in questions about the rms package for R (for Regression Modeling Strategies).

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Mean absolute error OR root mean squared error?

Why use Root Mean Squared Error (RMSE) instead of Mean Absolute Error (MAE)?? Hi I've been investigating the error generated in a calculation - I initially calculated the error as a Root Mean Normalised Squared Error. Looking a little closer, I…
user1665220
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How to interpret error measures?

I am running the classify in Weka for a certain dataset and I've noticed that if I'm trying to predict a nominal value the output specifically shows the correctly and incorrectly predicted values. However, now I'm running it for a numerical…
FloIancu
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Why does minimizing the MAE lead to forecasting the median and not the mean?

From the Forecasting: Principles and Practice textbook by Rob J Hyndman and George Athanasopoulos, specifically the section on accuracy measurement: A forecast method that minimizes the MAE will lead to forecasts of the median, while minimizing…
Brans Ds
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How to interpret root mean squared error (RMSE) vs standard deviation?

Let's say I have a model that gives me projected values. I calculate RMSE of those values. And then the standard deviation of the actual values. Does it make any sense to compare those two values (variances)? What I think is, if RMSE and…
jkim19
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RMSE vs Standard deviation in population

RMSE (Root mean square error) and SD (Standard deviation) have similar formulas. This link says The only difference is that you divide by $n$ and not $n−1$ since you are not subtracting the sample mean here. The RMSE would then correspond to …
JH.Kim
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Why is LogLoss preferred over other proper scoring rules?

It seems anytime people care about estimating probabilities accurately they choose LogLoss as the evaluation metric. But there are many other evaluation metrics which will prefer accurate estimation of probabilities (and not only ranking or…
Meir Maor
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Cross validation and ordinal logistic regression

I am trying to understand cross-validation for ordinal logistic regression. The aim of the game is to validate the model used in an analysis... I first construct a toy data set: set.seed(1) N <- 10000 # predictors x1 <- runif(N) x2 <- runif(N) x3 <-…
Elvis
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RMSE (Root Mean Squared Error) for logistic models

I have a question regarding the validity of using RMSE (Root Mean Squared Error) to compare different logistic models. The response is either 0 or 1 and the predictions are probabilities between 0-1? Is the way applied below valid with the binary…
Ahmed El-Gabbas
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Normalized RMSE

I have several time-series in a VAR(1) and, due to some of them haven't the same unit of measure, I'd like to estimate the RMSE in percentage. I know that it could be done in several ways (see below) but I don't know precisely which is the one that…
user40899
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What is the RMSE of k-Fold Cross Validation?

I am testing a neural net to predict numeric values. For that i am using a Training,Validation and Test split. I made a manual 4-Fold CV, this means i am getting 4 RMSE error, each one is the error of the i-th Fold on the test data. How do i get…
mognowich
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Using multiple imputation for Cox proportional hazards, then validating with rms package?

I've been researching the mice package, and I haven't yet discovered a way to use the multiple imputations to make a Cox model, then validate that model with the rms package's validate() function. Here is some sample code of what I have so far,…
JJM
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Can RMSE and MAE have the same value?

I am implementing cross validation and calculating error metrics such as RMSE, $R^2$, MAE, MSE, etc. Can RMSE and MAE have the same value?
Perl
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RMSE vs MSE loss function - the optimization solutions are equivalent?

If we optimize a function $f$ with respect to loss $L$, which is defined as RMSE; Are we going to get the same solution as optimizing MSE ? Even, if the function $f$ is non-linear (e.g. a neural network) ?
Daniel Wiczew
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Determine best ARIMA model with AICc and RMSE

I have done a training set to fit different ARIMA models and then a test set to assess their performance (with R). From what I understood, I can use the AICc to determine the best model by choosing the one with the smallest AICc, but the…
Aina
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Calibration of Cox regression survival analysis

To perform calibration of a Cox regression model (i.e. assessing for the agreement between the predicted and the observed outcome), what is the best method to present the accuracy of the model in predicting the actual event? As far as I…
user32454
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