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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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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33 views

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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18 views

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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10 views

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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19 views

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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1answer
78 views

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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1answer
91 views

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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62 views

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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25 views

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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36 views

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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1answer
64 views

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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1answer
99 views

RMSE is scale-dependent; is RMSE%?

I've got a graph of RMSE% vs. unit size and it declines nicely. Is this scale-dependence or does the "%" compensate for that? $$ \text{RMSE%} = 100\% \cdot \frac{\sqrt{\frac{1}{n}\Sigma_{i=1}^n (y_i ...
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44 views

compare different Imputation method by RMSE

My original dataset : ...
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33 views

Standard errors and confidence interval in cox regression model validation using RMS package

I am using RMS package of R to validate cox regression model with bootstrap. Please see the sample code below. I have three questions: (1) How do I request the standard errors and/or confidence ...
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1answer
49 views

Which denominator to use for cross-validated RMSE: $n$ or $n-k$?

I'm having a hard time understanding when I should take out the number of parameters from the denominator of the root mean squared error. From what I understood (other question, and wiki article), if ...
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19 views

Custom metric in Caret that puts more weight on bias

I am fitting a machine learning model that needs to have a low bias; variance is not as important. As such I would like to fit a model that places more weight on bias, than using the custom metric for ...
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12 views

Assessing a vector of errors in modeling

The quality of a model is often assessed based on a figure of merit such as RMSE. This reduces the individual errors in the model to a single number without assessing the errors as a population of ...
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80 views

How to interpret poor $R^2$ score but good RMSE value?

I split my data into training set and test set and am running linear regression on it. I am using Python's "scikit" library and I am getting an $R^2$ score of 0.31 and an RMSE value of 0.037. The ...
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2answers
31 views

How to apply a model from one data set to another

I'm still new to SAS, and I need to take a basic OLS regression from one data set, and find the RMSE when applied to a different set. This feels simple, but I haven't found anything. Help would be ...
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53 views

Shouldn't the root mean square error (RMSE) be called root mean square residual?

As far as I understand, estimating the error of a model, say an artificial neural network, requires to know the "true" model. Wikipedia says in its article "Errors and residuals": "The error (or ...
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1answer
35 views

How to request predicted points for each patient based on nomogram in RMS?

I am generating nomogram for a survival analysis project using RMS package of R. A PI of the project would like to have predicted points for each patient in the sample predicted by the nomogram. Is ...
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1answer
20 views

RMS and probability of steady values

Given an RMS value of a signal/waveform/list of numbers, I would like to construct an equation that calculates the probability that $n$ consecutive points are the same (or close). Suppose I have a ...
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101 views

How can I calculate the root mean square error (RMSE) for two covariance matrices?

I want to compare different methods of estimating the covariance matrices on the basis of RMSE and will recommend having the minimum RMSE. I have a sample of, say, 356 weekly observations of 10 ...
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66 views

Minimizing RMSE while using a log-transformation

I am trying to fit a linear model to some data, but the dependent variable y is clearly not normally distributed. It has a heavy tail on the right. A log-transformation helps to make the ...
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1answer
65 views

Is it possible to compare the RMSE of different models with different datasets?

I have 5 datasets and for each one of them I created 2 prediction models. For such task I divided each dataset in training and testing set (70/30%). Then I assessed the RMSE for each one and ...
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2answers
88 views

How to predict using ordered probit regression and calculate prediction accuracy?

I want to do an ordered probit regression, then cross-validate model prediction accuracy with 80% data for training and 20% for validation, and calculate RMSE for predictions. Consider this dataset: ...
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52 views

How to compare forecast accuracy of ordered probit and the equivalent Bayesian heierarchical model in R?

I have a dataset of a metric predictor variable $X$, and an ordered categorical predicted value $Y$ for several individuals. The dataset are from two groups $G_1$ and $G_2$. I want to estimate $Y$ ...
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179 views

How to discuss RMSE, MAE, $R^2$ results. What values are good/bad?

I have regression results for a study where I'm trying to develop a predictive model to estimate the value of a continuous output value for a physical process. My database has around 400 records and ...
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2answers
980 views

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 ...
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25 views

Standard performance measure for regression?

I will perform time-series prediction and I will report the accuracy of my system with a measure like RMSE or MAE. However, the variables I will predict are in different ranges. So let's say one is ...
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2answers
143 views

How to change baseline patient in Predict function in rms package in R?

I am doing a time dependent Cox model using cph function in rms package. I use Predict and plot.Predict to plot the hazard ratio on y axis and a continuous covariate (e.g. LDL cholesterol) on X axis ...
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70 views

Root-Mean Squared Error for Bayesian Regression Models

I'm trying to get a sense of my prediction errors for a Bayesian regression model and I was using the Root-Mean-Squared Error. My question is, since are predictions are stochastic, would it make ...
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1answer
56 views

Using {rms} package for multinomial logit

Is it possible to use the rms package to model multinomials logits, or elsewise to model several binary logits to achieve the same effect? I am aware that there are many other packages specifically ...
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1answer
66 views

Visualizing nonlinear regression

I have following model using mtcars dataset: ...
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59 views

What measure to use in finding the best linear model

I have a bunch of linear models (say 20 of them), and a bunch of datasets (e.g. 400). I wrote a code in R so that each dataset is exposed to each model, and the goal is to select the best model that ...
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165 views

KS, RMSE tests in R

I have a set of yearly peak river flows and I am trying to use the KS test to conclude if the data is coming from a generalized extreme value (GEV) distribution. I am also trying to calculate a root ...
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1answer
65 views

Can there be a situation where one regression model gives lower RMSE than the other but also lower R-squared?

Consider the following scenario where you use the same data X (the same number of predictors p, same number of observations ...
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1answer
466 views

what is the meaning of RMSE in caret::train [duplicate]

I'm confused by the exercise solutions of the book Applied Predictive Modeling. In https://github.com/topepo/APM_Exercises/blob/master/Ch_06.pdf at the beginning of page 4 ...
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74 views

Recommendation system and baseline predictors

I'm participating in programming contest, where I have a data, and where the first number is a user, second number is a movie, and the third is a number in then-points rating. ...
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1answer
48 views

RMSE normalisation, what method prefer?

According to this article on wikipedia http://en.wikipedia.org/wiki/Root-mean-square_deviation, two methods are widely used to normalise the RMSE. The first is dividing by the range: $$NRMSE = ...
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1answer
75 views

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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3answers
246 views

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 ...
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1answer
7k views

How to interpret error measures in Weka output?

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. ...
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1answer
187 views

MSEP and R2pred for Linear Model

I have two set of data 1-Training (Calibrating) 2-Test. With these datasets, I Fit the model using first dataset. predict using the second dataset x-variables I have to test the closeness of the ...
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153 views

Multiple Imputation - Help Needed

These multiple imputation results relate to data I have previously described and shown here - Skewed Distributions for Logistic Regression Three variables I am using have missing data. Their names, ...
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42 views

Absolute Loss in R

I have been asked to compared between Robustness of absolute lost regression and its variants compared to least squares. I have done the least squares should I use Lasso now? ...
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98 views

Calculation of RMSE for Weibull distribution model

I'm currently studying Weibull distribution and I have questions regarding 'statistical tests' (RMSE for now) for Weibull distribution. First, I want to be clear on one thing here. What does 'actual ...
4
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63 views

What is the “pdm” stat in the “rms” R package?

I am new to the world of Regression in statistics and I have been doing a research in which I am building an ordinal logistic regression model (ORM). In order to fit my ORM model, I am using the 'orm' ...
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90 views

Coefficient of determination contradicts the normalized RMSE

I have a model that allows me to estimate the values of a signal and I’m testing it under different environmental conditions. To compare my estimated signal to the real (reference) signal I’m using ...
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20 views

How to separate model errors from measurement errors?

I've got data measured with errors that have known measured_RMS. I am testing a model that has model_RMS differences between model prediction and measured data. What would be a reasonable estimate of ...