Questions tagged [error]

The error of an estimate or prediction is its deviation from the true value, which may be unobservable (e.g., regression parameters), or observable (e.g., future realizations). Use the [error-message] tag to ask about software errors.

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25 views

How can I reduce the noise of prediction graph? [duplicate]

I am trying to use LSTM to predict a time series data as you can see in the following image, the predicted graphs is very noisy: The original data is looking like this: That I normalized it like ...
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19 views

How can I compare the effectiveness of a regression model for different datasets

I have a multiple linear model that works on different datasets. suppose that the first dataset produces y in range of [1,100] and the second one in range of [1, ...
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How to measure the variation of a signal as a percentage

The flat curve in the following figure indicates a signal that changes with a variable Vx. The signal is the sum of the other two signals shown in the image. As shown the signal stays fairly constant ...
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4answers
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why there is no “error” term in survival analysis?

Where is the error term behind the following model: $$h_i(t) = h_0(t) \exp \left ( \sum_{k = 1}^p \beta_k z_{ik} \right )$$
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154 views

Alternatives to minimizing loss in regression

We know that loss (error) minimization originated with Legendre and Gauss in the early 18th c. More recently Friedman* extolled its virtues for use in predictive modeling: “The aim of regression ...
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14 views

How to statistically compare the accuracy of different methods?

I have a fairly basic understanding of statistics so I appreciate any help I can get. I'm trying to compare two different methods (A and B) of placing physical objects accurately. After the objects ...
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1answer
35 views

How to measure the variance of error?

So I have a predictive model generating a list of $\hat{y_i}$, and the error of each forecast is $\hat{y_i}-y_i$. I would like to measure the variance of the errors. This can be calculated by $$\...
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how to evaluate or fulfill required accuracy for regression aka precision of estimation?

Maybe there is already a question similar to mine but there are so many involving the term accuracy and at least none, except of How to evaluate instrumentation accuracy? , didn't seem "very" similar. ...
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Error in the mean of uncertain results from cross validation folds

I have a dataset and some candidates I want to make predictions for. I have done 5-fold cross validation to assess the model's performance. However, when I make predictions for the new samples I am ...
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1answer
46 views

What is the definition of this statistic?

For a data set that is Gaussian distributed, $\sigma$ defines the standard-deviation of the distribution. My question is, what is the correct indention or terminology for the following: $$\frac{\...
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2answers
35 views

Choosing error bars when the random variable has asymmetric distribution [closed]

I have a simulation data for a random variable $X$, and also a parameter $p$. I am plotting the average $\langle X\rangle$ vs $p$. Now, I also want to show error bars on the plot to show the spread of ...
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How to include image errors in convolutional neural network?

I'm using convolutional neural networks in order to classify astronomical sources directly from the images. For each image I've a weight map, i.e. an image with the same shape, whose pixels are ...
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1answer
10 views

Determining which methods to use to find how close a day is from the average pattern

Would anyone have advice on how to determine how close a day is to matching the average pattern of all days? I would like to take each day of the year and evaluate how close that day is from the ...
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How to describe accuracy/error without ground truth?

I am using machine learning regression models to predict motor scores among a population with spinal cord injury using features derived from their actual movements. Although the clinical measure we ...
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1answer
29 views

error estimate or confidence interval on a probability

Imagine I have $N$ 6-sided die, all identical but not fair, so that the probability of getting 1 is $P(1)$, the probability of getting 2 is $P(2)$ etc. I would like to run an experiment (rather than ...
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Error margin calculated from individual errors/residuals

Say I run a model and then calculate the residuals or the errors between what my model predicted and the real-world results. For example: ...
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1answer
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Can MAD (median absolute deviation) or MAE (mean absolute error) be used to calculate prediction intervals?

From my understanding, RMSE (root mean square error) estimated through cross-validation can be used to calculate the prediction interval of a mixed-effect linear model with gaussian error. In my case, ...
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1answer
58 views

How to compute a confidence interval on the regression error?

I have a regression model (not necessarily linear regression) and a test set. I would like to be able to say: "If you use my model, then with probability 95%, the prediction error will be in the ...
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1answer
38 views

Low Bias in an overfitted model

I have a question about the bias-variance tradeoff in machine learning concerning the implications of overfitting: Assuming $y = f(x)$ + some noise, the error of our model for any input $(x,y)$ is ...
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1answer
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What is the correct definition of the root mean square percentage error (RMSPE)?

Göçken et al. define the root mean square percentage error (RMSPE) as \begin{equation} \text{RMSPE} = \sqrt{\frac{100\%}{n} \cdot \sum_{i=1}^n \Delta X^2_{\text{rel},i}} \end{equation} with \begin{...
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Is there something like a Root Mean Square Percentage Error (RMSPE)? Or: What is the name of this error? [duplicate]

\begin{equation} \text{RMSPE} = \sqrt{\frac{1}{n} \cdot \sum_{i=1}^n \Delta X^2_{\text{rel},i}}\cdot 100\% \end{equation} with \begin{equation} \Delta X_{\text{rel},i}=\frac{X_i}{T_i}-1, \end{...
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1answer
60 views

Is there something like a Root Mean Square Relative Error (RMSRE)? Or: What is the name of this error?

\begin{equation} \text{RMSRE} = \sqrt{\frac{1}{n}\cdot\sum_{i=1}^n \Delta X^2_{\text{rel},i}} \end{equation} with \begin{equation} \Delta X_{\text{rel},i} = \frac{X_i}{T_i}-1, \end{equation} where $...
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41 views

Propagating error when taking the derivative

I have a function that corresponds to a set of $(X,Y)$ coordinates with a Gaussian uncertainty ($\sigma_Y$) for each point. What I want to do is now compute the gradient of this function and the ...
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1answer
23 views

Autocorrelate relative difference between two time series

I would like to verify the similarity of two time series. So far I have resampled and interpolated one time series, so that the two have synchronous time. Next I have computed the relative difference ...
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1answer
40 views

Determining the standard error of a ratio of means [duplicate]

I hope that this request will make sense. I am not extremely proficient in these kinds of stats, so please also excuse my limited vocabulary. I have two datasets, we'll call A and B, and for each ...
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19 views

Error propagation in simulation-based approach

I am working with a method which, in one of the steps, takes as input some aggregate-level data, e.g. means and standard deviations for the covariates of a specific population and the marginal ...
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MSE series derived from cross validation on time series

This answer suggests a way of doing leave-one-out cross-validation on time series data: An approach that's sometimes more principled for time series is forward chaining, where your procedure ...
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56 views

Does anybody know this measure of model fit / prediction error?

Let $y_i$ be the true value and $\hat{y}_i$ a prediction from a model. Then, for example $$B=n^{-1}\sum_{i=1}^n \hat{y}_i - y_i$$ is the prediction bias and $$MSE=n^{-1}\sum_{i=1}^n (\hat{y}_i - y_i)^...
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1answer
56 views

Clustering without test set and evaluation

I have to classify some data without any futher prediction (I just need the best clusters on the data). Do I still have to train-test-split my data or do a kfoldCV? And how do I evaluate my ...
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1answer
62 views

Error sum of square for OLS estimator

The error sum of squares is defined as: $$ SSe(\beta)=(y-X\beta)'(y-X\beta)\tag{1}$$ I want to show that for the OLS estimator $\hat\beta$, $$SSe(\beta)=SSres+(\beta-\hat\beta)'X'X(\beta-\hat\beta)\...
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1answer
13 views

Is there a signed (ie anti-symmetric) version of SMAPE?

The symmetric mean absolute percent error (SMAPE) is a symmetrized version of percent error with the formula: $$\frac{200\%}{n}\sum_i\frac{|x_i - y_i|}{|x_i| + |y_i|}$$ SMAPE is symmetric: ...
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30 views

GLM errors: no valid set of coefficients and In log(ifelse(y==0,1,y/mu)):NaNs produced

I am trying to determine which variables influence my response variable droms for individual lizards in 6 sites across 6 years. I am using a glm as my response ...
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1answer
115 views

Singular gradient erros, NLS in R

I'm trying to fit nls(Mound~ a*kg.bag.collar^b + c, start = list(a = 83, b = -.5, c=100), data=test) using the dataset here. I've fit it without trouble without the ...
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1answer
32 views

How to calculate intra-observer error and average difference?

I am trying to assess intra-observer error in a setting where measurements where done repeatedly by a single observer. So far I'm having some conceptual and technical issues. In the dataset we have ...
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9 views

error residual identical for within subject ANOVA and between subject ANOVA with double the sample size

I noticed something interesting while playing around with data. If I conduct a 2-by-2 within subject ANOVA with 20 subjects my sum of square residuals look like this: ...
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1answer
47 views

Is the difference between the residual and error term in a regression just the ability to observe it?

According to what I read online, the error term and the residual are often interchangeable. Please let me know if my understanding below is correct: However, the difference is that the error term is ...
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1answer
31 views

Question about the Multiple Linear Regression: why and how does it work?

I know this question is quite simple and maybe quite naive as well, but I would like to get some help. The general linear model can be expressed as \begin{align*} \textbf{Y} = \textbf{X}\beta + \...
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37 views

error of Monte Carlo estimate of root mean square speed (vrms) of ideal gas

I am trying to use Monte Carlo method to estimate the oot mean square speed (vrms) of an ideal gas, the speed of an ideal gas follows the Maxwell-Boltzmann distribution: $$p(v)= \frac{4}{\sqrt {\pi}}(...
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0answers
23 views

Propagating Uncertainties on Interpolated Data

I have a data set of 2000 $[x, F(x), \delta F(x)]$ triples, where $x$ is exact and $F$ is a measured value with an uncertainty $\delta F$. I can interpolate/fit the function however needed, and this ...
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32 views

Split split plot: defining expected Mean Square error term for calculation of F values

Note: my endgoal concerns multivariate analysis but I do not believe my question is specific to this setting Motivation: the RRPP R package allows to analyze composition data (i.e. multivariate) ...
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25 views

MLE estimate for least squares if features have Gaussian noise

We have come across the problem of MLE estimate for least squares if errors are normally distributed, eg, $Y_i=\beta x_i+\epsilon$, where $\epsilon$ ~ $N(0,\sigma^2)$. The estimate for the above case ...
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10 views

Deterioration of the accuracy of a system over time

I have a system that compares the predicted variable with the true variable by calculating the absolute error percentages. . Where $\pi$ is the predicted variable and P is the true variable. And you ...
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1answer
40 views

Is a Type III statistical error just a subset of Type I or II error?

I have recently come across the idea of a type III error through discussion with colleagues. The definition they gave me was something along these lines: "Type III error occurs when you correctly ...
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Error bars of Monte Carlo expectation with correlated samples

I will try to phrase the question in a general way, then give my specific case as an example. Suppose I want to evaluate $Q = \mathbb E \left[ f\left(X, Y \right) \right]$ where $X$ and $Y$ are ...
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1answer
17 views

The combined SEM of two averages with SEM

I am looking to calculate the difference in blood flow between the controls and intervention group (dipyridamole) and whether this is significant. The table 2 shows the average blood flow + SEM each ...
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55 views

R: H is singular

For my thesis I need to estimate BEKK GARCH models. For this I have tried several packages. I keep getting the same error: "H is singular". I have found that this can be caused by highly correlated ...
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16 views

How can I use repeated cross-validation to report out-of-sample prediction performance?

I'd like to better understand how to report the out-of-sample prediction performance using repeated k-folds cross-validation. I think I have a reasonably good understanding of the motivation for ...
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1answer
78 views

How can I test for autocorrelated errors in logistic regression?

I'm doing a Bayesian logistic regression $Y \sim X$ where my predictor $X$ is a count observed over time. So $Y$ and $X$ are each $m x n$ matrices where $m$ is the number of subjects and $n$ is the ...
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1answer
37 views

Which approach should be used to compare two different measurement techniques of same samples?

I have individually measured failure forces of 8 materials and those recorded with A method and B method in same time: 8 results in each method, A=8 and B=8. The range of data of both measurement ...
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1answer
40 views

what is the difference between Standard error of the means vs Sampling error?

I am confused after learning about the different terms. I understood Standard error of the means to be the Standard Deviation of the sample means, whilst Sampling error is the Standard Deviation ...