# Tagged Questions

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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### 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 ...
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### What measure should I use to compare two sets of calculations?

Assume I have two sets of calculations produced by two different simulators. There is no way to precisely measure actual values for these calculations, so I'm defaulting to the assumption that one of ...
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### Comparing RMSE to model

I'm assessing the accuracy of the prediction of my model using the RMSE on a new data set. Now the RMSE in itself doesn't give any indication of whether it is a good model since there is no threshold ...
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### Correct Grammatical Form for RMSE? [closed]

Which is preferred for use in journal publication: Root-Mean-Square Error or Root Mean Squared error? Root-mean-square sounds a little casual, like "ice tea" instead of "iced." On the other hand, ...
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### Why does RMSE underestimate model variance?

I have read that RMSE of calibration/validation/cross validation is frequently used for model selection (e.g., for ANN), but can lead to over-fitting because the prediction error represents the ...
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### Cross Validation Train Test Gap Question

Question: is minimizing test set mean validation error more important than the gap between train and test errors? Let's say I can tweak parameters in my model to give me mean validation error of 4500 ...
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### Using a combined RMSE?

I have 12 soil water sensors with a few years of actual soil water samples that have been retrieved from near each of the sensors. We have found that individually regressing the data from each sensor ...
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### How to identify the prediction equation from a regression model using splines

I find it difficult to connect the coefficients of a regression model that includes splines to the actual prediction equation. For example, how could that be done with the following model? ...
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### What are the bias and variance of a model returning the observed mean for a training set?

It seems to me that bias = variance = 0 but MSE > 0, possibly very high, so clearly my intuition, and math, are wrong. For a training set $T$ and a regression problem let $M(T) = \text{Ave}(y(T))$. ...
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### Interpreting RMSE and MAE values

Returns of a index, where daily returns ($R_t$) are defined as $R_t:=\log(P_t/P_{t-1})$. And daily volatility ($\sigma_t^2$) is defined as $R_t^2 = \sigma_t^2$. After an evaluation of a naive ...
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### How to see if my calculated values match the actual value?

I wanted to confirm that I was using the right statistics to measure the whether or not our experimental model of calculating the speed of sound was accurate. We experimentally calculated the speed ...
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### Notation for computing MSE confuses me?

I wish to compute MSE of my models. Say my data was generated from the following model: $y_i=f(x_i)+e_i$ where $e_i$ is some noise around the true relationship \$...
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### Evaluate forecasting ability of GARCH models with RMSE and MAE

I am evaluating different forecasting models and their ability to forecast index volatility during period of market turmoil, using two measurements, Root Mean Square Error and Mean Absolute Error. For ...
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### cross validation and validation( to find RMS error and correlation ) in matlab

Dear Experts; i have text data (sample points are 324) of different climatic parameters. 3rd column of each text file was contained some missing or NaN data. Using Scatter data interpolation in ...
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### Very Large RMSE with Linear Regression

I am working on a regression problem that has about 180 binary features and approximately 280,000 data samples. For certain train-test splits of my data, the resulting linear-regression model (...
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### RMSE vs R Squared literature

I have found many related answers and explanations, but not one that involves literature. I have a model and I have used cross validation. Some models have really high R and adjusted R squared values, ...
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### How to use RMSE when having data normalization?

I am new in machine learning and I am studying time series prediction using neural networks. Pseudocode 1: ...
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### How does Stata calculate RMSE in regression with weights?

This problem came up because I was trying to replicate some results I was getting in Stata with R, and I was able to replicate everything except for the root mean squared error. When I run a ...
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### Comparing linear and nonlinear models

Is it possible to compare between these two types of model? I have a set of data that involves 6 independent variables and 1 dependent variable. It is based of a questionnaire for social science ...
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### Smaller standard errors *after* multiple imputation?

I have 1771 observations, with 30% missing data for x1 (Yes:No), and no other missing values from 26 other variables (mix of continuous and factor). I am using quantile regression in R, with and ...