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 ...
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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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Cramer-Rao bound (CRB) and Root-Mean-Square-Error / Mean-Square-Error (RMSE / MSE)
My question is regarding the comparison between the CRB of a given vector parameter and RMSE/MSE obtained from Monte-Carlo (MC) simulation. The approach I used is this:
For $\boldsymbol{\theta} \in \...
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Longitudinal RCT modeling of continuous time
I have data from an intervention study (10 clinics, 5 control, 5 treatment). The outcome is counts, and we have monthly data at baseline, treatment active phase, and post treatment phase. The number ...
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Should the RMSE of an unrestricted VAR model decrease as compared to a restricted Autoregression model when there is Granger Causality
I have 2 time series, say for instance, T1 and T2. T1 granger causes T2 at lag 2. Should this mean that if I make a VAR model with these two time series, and an autoregression model with just T2, the ...
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Should the RMSE of the unrestricted (VAR) model for a time series that is being Granger caused by another be lesser than its restricted counterpart?
I have a couple of time series, say, T1 and T2. I have established (using the grangercausalitytest library of Statsmodels in ...
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(Un)Calibrated Logistic Regression Fit
I'm fitting a logistic regression on a large dataset (n=89260, 17 predictors) with a class imbalance (1% positive class). I've tried to follow Dr. Harrell's teachings so I fit my full pre-specified ...
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Error propagation from P-V error to RMS error [duplicate]
I have a question about the Error propagation in RMS.
My surface profilometer has P-V error with 100 nm (It follows gaussian distribution).
And I investigate the z-axis positions of the object surface ...
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problem forecasting in R using a VAR model : interpretation of characteristic polynomial roots
I have the following R code, I am fitting a VAR(10) models to a bivariate time series, comprising two variables, gaz and nuc. Yet, when trying to forecast, I had negative values, whereas my series is ...
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Comparing RMSE values across different datasets
I am working on a PV energy production forecasting problem. With various ML models (ANN, RNN, LSTM) I am trying to predict the energy for the following day, based on the historical data.
The ...
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Is there an error metric that decreases the weight when the target is near zero?
As precipitation prediction models can only predict positive values, they won't be able to undershoot small values by much. When it comes to overshooting, there is no boundary. High precipitation ...
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RMSE model interpretation
Let's say I train a model and it has an RMSE of 2.5.
Does this mean, that on average, my prediction will be 2.5 away from the true value? Or does some scaling need to be done in oreder to get this ...
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Why the results of Cox regression are different between coxph() and cph() in rms package
I found the predicted hazard (the h(t) of Cox regression) through Predict() and cph() in rms package was different from common coxph().
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Searching for references that show imputation methods use RMSE as distance measures for ordinal data
RMSE or MAD are used as distance measures more for the continuous data. What will be good distance measures for ordinal data?
Are you aware of any good references that show imputation methods also ...
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Obtaining 12 month ahead in sample RMSEs
I am attempting to recreate the results of the paper written by King, Stock and Watson in 1995: Temporal instability in the unemployment inflation relationship.
The paper estimates a VAR model with 12 ...
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Cox model: how to model treatment variable when timing is unknown
We have cancer medical registry data, including information on date of diagnosis, treatment, and followup e.g. date of death etc. However, we only know type of treatment received for each person. We ...
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Restricted cubic spline looks like a linear curve, but p for nonlinear < 0.001
I am analyzing a association between a frailty index and care needs using the cox model. I use R and use rms package to fit restricted cubic spline.
This is my R code.
...
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ROC with bootstraping
I have a data with 2 variables: diagnosis- yes/no
Score- numeric variable from 0-10.
I need to do ROC analysis for this data and to find the best cut off values.
The problem is the data is too small ...
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Get the R2/RMSE for each category of a dataset
This might be a dumb question !
I built a model and I'm satisfied enough with the model, given that I have a dataset with categorical variables I wanted to see the R2/RMSE for each of those categories,...
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How do you interpret the value of RMSE/MSE in English to stakeholders?
For example, if you have a R^2 of 0.95, you can explain this number to stakeholders in a presentation as:
Our model explains 95% of the total variance within the data.
However, if we have a RMSE of 11,...
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Why RMSE and MAPE changes with the change of axis?
I need your help regarding the information inside the picture. As you know all the information will change with the change of NDVI axis from y-axis to X-axis, except R2 and p-value remain the same? ...
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How do we relate RMS and standard deviation for continuous signals?
Because the discrete formula for RMS, $\displaystyle X_{RMS}=\sqrt{{1 \over N}(x[1]^2+x[2]^2+...+x[N]^2)}$, is almost the same as the formula for standard deviation (assuming mean zero), except for a ...
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What values of the independent variable do I use to compute the predicted data when calculating RMSE?
I have a data set with
x = [10 16.25 16.25 16.25 16.25 20 22.5 22.6875 24.57 24.57 41.86 47 47 53.8 66.43 77.9 91.201 96.2 97.2]
and
y = [1.28 4.15 3.42 1.53 3.44 4.89 2.91 8.51 9.03 14.91 9.73 8.07 ...
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Comparison of RMSE (root mean squared error) values
I want to see if my models work better univariate or multiple. But how can I do this? Normally I train the model, calculate the RMSE/MSE on the test data and compare these values. Now I trained the ...
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Summarizing a set of root-mean-squared error values
From simulation studies, I have repeated (1000) measures of the root-mean-squared-error (deviation) between a sample of observed values and the predicted value. The obtained RMSE values are, naturally ...
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Interpret R Squared and RMSE
I am relatively new to using the MLTK app on Splunk.
When trying a number of example, I ran a regression that uses "ac_power" to predict "total-cpu-utilization". I receive the ...
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I need help to compute the RMSE of lasso model [closed]
I was following this other example on how to find lasso regression in r . The image posted below is the image of the codes. I need help with find the RMSE
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Is it possible to generate a scatterplot of relative hazard for participants superimposed on Cox regression line?
I have been using the rms package in R to perform Cox regression on time-to-event data. I have used the ...
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Understanding & Usefulness of Residual Standard Error
So I am trying to deeply understand the concepts of Residual Standard Error (in addition to RMSE) as well as their usefulness. Here is my current understanding:
RMSE - the standard deviation of the ...
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Cross validation on bootstrap data
I am performing a dirichlet model for different species using a small sample size (between 8 to 20 samples per each).
Since my dataset is small, I bootstrap my data with 1000 iterations, averaging 3 ...
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How to interpret R-squared versus nRMSE for a random forest model?
I have trained six random forest regression models (to predict topsoil, subsoil and total soil organic carbon stocks for two study ares) using out-of-bag validation, and I have gathered the R² and ...
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How do we know if the RMSE values are reliable? [closed]
The root-mean-squared error(RMSE) values should be close to zero. Although the optimal value of RMSE is known as 0, we can say that it is low when RMSE =10 for the data set with high average (let’s ...
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RMSE for model-selection
Can I use RMSE,r2 or other metric to compare models of different datasets and variables?
And if I have the same dataset but different variables?
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Relation between validation set loss and Test loss in Machine learning
I am very new to Machine learning. I am trying to implement a feedforward neural network to predict release year of songs based on some audio features.
I have a train.csv file and dev.csv file. I use ...
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Using bootstrapping to calculate the AUC of a ridge regression model
Edit:
I have a RNA-seq dataset with 8k genes and 100 samples (60 samples with disease condition 1 and 40 samples with disease condition 2) and I am trying to predict a dichotomous disease status.
I'd ...
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A Higher r-squared always implies a reduction in MAE and RMSE?
I apply 2 different machine learning models in my data, a Multiple Linear Regression and Random Forest. The results were bellow:
Why the MAE and RMSE are higher for a higher R-squared? Both models ...
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Restricted Cubic Splines with 3 knots
I have started studying cubic splines and I am confused. If I have 3 knots according to the theory I should have K-2 = 3-2 =1 polynomial. When I use the rms package in R there is indeed one polynomial....
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RMSE and R2 with different training splits
I am running 2 linear regression models using the same data with different data splits. n=205
70/30 split
RMSE: 2341
R2: 0.85
50/50 split
RMSE: 2474
R2: 0.88
Seems counterintuitive that the R2 ...
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How to interpret RMSE with scaled values vs ground truth values
I've trained an LSTM model and am measuring RMSE. I know how RMSE is interpreted normally, but I'm a a little confused on how to interpret the RMSE value when I have scaled my features and target ...
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Percentage change in RMSE (or MAE) over models
Let's say I have two different models of an outcome Y, m1 and m2 and perform some kind of cross-validation.
I calculate the RMSE and the MAE on the test set (for the two models) and I want to say ...
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How to interpret MSE, RMSE and MAE
I understand in general MSE, RMSE and MAE means average distance between the actual and predicted value, and the lower the MSE, RMSE and MAE, the better the model fits the dataset.
I try to understand ...
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Training RMSE is almost 5 times as high as test RMSE - need help understanding why
I am currently trying to model the median_house_value (MHV) from a California data set from the 90's. But the training RMSE (230142) is almost 5 times as high as ...
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MAE or RMSE for my data? [duplicate]
I have been checking how each error metric works in the hope to find the best one for my data but it can be quite tricky actually.
I have monthly time series data and I am running a SARIMA model to ...
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Why do you take the sqrt of 1/n for RMSE?
Updated question:
Why do we use RMSE:
$$RMSE = \sqrt{\frac{1}{n}\Sigma_{i=1}^{n}{\Big(\hat{y}_i -y_i\Big)^2}}$$
Why is it not MRSE:
$$MRSE = \frac{1}{n}\sqrt{\Sigma_{i=1}^{n}{\Big(\hat{y}_i -y_i\Big)^...
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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 ...
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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:...
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Comparing RMSE/MSE of original data and log10-values of the same data
I want to see if my models work better on the original data or on log10 transformed data. But how can I do this? Normally I train the model, calculate the RMSE/MSE on the test data and compare these ...
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Showing RMSE and MAE results as percentage error
I have the results of RMSE and MAE from different spatial interpolation methods as a monthly averages (See the figure below). As ...
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