# 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)

175 questions
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### Why using RMSE as loss function in logistic regression takes non convex form but doesn't in linear regression? [duplicate]

I am taking this deep learning course from Andrew NG. In the 3rd lecture of 2nd week of the first course, he mentions that we can use RMSE for logistic regression as well but it will take a nonconvex ...
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### Help with saving stats in rms bootcov [migrated]

I'm trying to save the distribution of R2 values as I bootstrap a model, using the ols and bootcov functions in the rms package. ...
0answers
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### Interpreting RMSE across a range of values

Imagine I have predicted values from a model. They have a gaussian distribution and range from 1-100. Comparing the predicted to the original variable, I calculated the root-mean-square-error (rmse) =...
1answer
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### Explain Root Mean Square Error to non-technical audience

My company is in the process of switching equipment from one vendor to another. We measured several metrics from the existing and new equipment and compared the time series. The ideal is to have no ...
3answers
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### Does the RMSE formula have a $k$ in the denominator?

In what circumstances does the RMSE formula have a $k$ in the denominator? StackOverflow's What does RMS stand for? shows this formula for RMSE: $$RMSE=\sqrt{\frac1{n-k}\sum_i(y_i-\hat{y}_i)^2}$$ ...
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### Normalised Root Mean square error

I have $10$ people in a group and they undergone a surgery. I have the root mean square of each subject before and after the surgery. ...
1answer
6 views

### rmse of differenced vs undifferenced data

if I created a forecast on a differenced data set and compared that to the differenced holdout set, would this rmse be the same as if I reverted back to the undifferenced data and then performed the ...
1answer
48 views

### Calculating RMSEC and RMSECV of PCA in R

I have been trying to calculate the root mean squares error of calibration (RMSEC) and the root mean squares error of cross validation (RMSECV) for a PCA model made in R using the mdatools package. ...
0answers
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### Cross-validation of (Cox) survival model with very high censoring rate

I am currently working on survival analysis of data with very high censoring rate (~99%), and the number of events is only about 500, using R. I would like to ask in such case, whether the validate() ...
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### aregImpute or mice for imputation of survival data

I would like to use multiple imputation to analyse associations between an exposure variable (exp) and different disease risks in a dataset with some missing data (...
0answers
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### How can RMSE be compared between a regression model and a neural network model?

In the calculation of RMSE, linear regression uses degrees of freedom(n-p) as divisor and neural network(feed-forward in my case) uses the total data number(does it have degrees of freedom as well?). ...
1answer
153 views

### Is it possible to find Normalized Root Mean Square Error (NRMSE) of Root Mean Square Error (RMSE) in R?

I have code in R that calculates the RMSE from a Linear Regression model: ...
1answer
176 views

### calculating overall error in k-fold cross validation

when using k-fold cross validation i thought the overall error was equal to the mean of errors of each fold. the error being anything from MAE and RMSE to NDCG,F-measure, precision and recall. however ...
0answers
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### caret chooses non-optimal RMSE?

I run a linear regression via caret / glmnet method with "RMSE" as metric. In the final model, caret tells me which values of the tuning parameters alpha and lambda were selected to minimize RMSE. If ...
1answer
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### How is probability y = j|X calculated from an ordinal logistic regression model?

I have an ordinal logistic regression model fitted with lrm from the rms library in R, and am presenting results as prob y = j|X ...
0answers
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### How to best evaluate a cross validation of a logistic regression using cbind

I ran a logistic GLMM using cbind for the response: ...
1answer
29 views

### What statistical test do I need for comparing forecasted data with actual data?

I’m currently completing my dissertation and need to compare forecasted wave height to the actual wave height. However I am unsure what statistical test to use. Thanks, Jess
0answers
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### Trend in residual plot

I have a regression problem: I have to predict for how long (in days) a house will stay in the market before that someone will buy it. To predict how many days the house stays in the market I am ...
0answers
42 views

### What is the point of using PRESS instead of RMSECV?

What is the point of using predicted residual sum of squares (PRESS) instead of root-mean-squared-error-of-cross-validation(RMSECV)? In many books, especially in the area of chemometrics, the authors ...
1answer
17 views

### Why compare measures of dispersion with ratios?

I'm writing a paper on a novel statistical model estimated using MCMC and am currently evaluating it using simulated data. We are comparing the performance of our model to an established model as ...
1answer
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### Comparing the RMSE produced by two models

Suppose I have two models, each of which have the purpose of estimating a sequence of magnitudes. Suppose further that there are $N$ such magnitudes to be estimated, and that each magnitude is know to ...
0answers
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### Comparing the RMSE produced by two models [duplicate]

Suppose I have two models, each of which have the purpose of estimating a sequence of magnitudes. Suppose further that there are $N$ such magnitudes to be estimated, and that each magnitude is know to ...
1answer
460 views

### Interpreting RMSE of log-values

I am modelling a regression with a GBM and evaluate by RMSE. My model input & target is log-transformed which results in an RMSE that is also on log-scale. How can i interpret this in an ...
1answer
48 views

### What is the best way to test and validate a multivariate regression using OLS?

I am implementing a multivariate regression from scratch using Ordinary Least Squares to get the weights. I noticed that this method does not have any hyperparameters to tweak, so I am not sure what I ...
2answers
668 views

### Random Forest “out of bag” RMSE

Normally, I used a test set to calculate the RMSE of my RandomForest model. But currently I am using the whole data set in the Random Forest. I want to validate (RMSE) my model with the "out of bag ...
2answers
42 views

### Performance evaluation

I'd like to test the performance of a penalized regression. I did three separate regressions for each response variable (one numerical, one binomial and one multinomial). I was checking this link, and ...
0answers
21 views

### Can i calculate the RMSE of two sets of mean values

I measured the tree heights for 13 forest plots in 2018 and want to compare it with the extrapolated reference data from 2013 to see how accurate my method is. I cannot calculate the RMSE of each ...
1answer
361 views

### How to test if two RMSE are significantly different?

Say I have two models for a regression task and from each model I get a RMSE. One RMSE is smaller than the other, however I wish to test if the difference is statistically significant in order to be ...
0answers
17 views

### Missing measurements in nonlinear chemical processes

I am using an imputation method to handle missing measurements;TSR.The prediction model used is LW-PLS. Based on the my results, the RMSE increases when the percentage of missing measurements ...
1answer
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### Is Spearman's rank and RMS error an appropriate measure of similarity between two signals?

I am working on a project comparing the accuracy of two imaging techniques to measure displacement. I have attached a graph comparing the displacement measured by both techniques over time. I am ...
0answers
139 views

### Why is the penalty in the logistic regression likelihood ratio test different from the penalty I specified when fitting the model?

I'm fitting a penalized logistic regression model using the rms package in R. When I print the result, the penalty in the model likelihood ratio test is different from the penalty I used to fit the ...
0answers
259 views

### Measuring accuracy for forecasting in R [closed]

I have a dataset of restaurant orders. In that data set I need to predict the outcome of the next 12 months, i.e. how much order will be given. using the following test ...
0answers
24 views

### 2nd degree polynome instead of restricted cubic splines

I am looking for an alternative to restricted cubic splines, which can provide a numerical result that is easier to interpret and compare (as far as I understand, this is not easily possible with ...
1answer
132 views

### same cross-validation set for parameter tuning and RMSE calculations

I miss some very basic distinction between cross-validations used for parameter tuning and cross-validation used for calculating the performance of my algorithms (RMSE). I have two functions: one ...
1answer
74 views

### How to determine whether difference in RMSE is meaningful

I often run into the situation where I have several regression models, each of which gives a RMSECV, and I need to choose which one is "best". Of course, I can choose the one with the minimum RMSECV, ...