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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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Computing a derivative and its associated gradient with Gaussian process regression in scikit

Are there any recommended methods for computing the derivative and its associated error when applying Gaussian process regression in scikit-learn? For instance, following the example here, one can ...
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1answer
13 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
9 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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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
42 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
30 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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14 views

Representing a dataset with non-normal errors

I have looked at several sources and cannot find any guidance, but perhaps I'm using the wrong terminology. I want to represent a dataset by regression line and variation similar to the way you would ...
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16 views

How to visualise uncertainty on error plots summarising multiple mcmc simulations [closed]

I am plotting the non-integer outputs of parameters x, y and z computed across 100 simulations for subjects A to E (via mcmc). My plot shows error on the y-axis, and subjects A - E on the x axis. ...
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17 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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12 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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22 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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24 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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3answers
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How often can a fixed test data be used to evaluate a class of models training on a fixed training set

Suppose I have a fixed training data set $D$ and a fixed test data set $F$ as well as a validation set $V$ and suppose I have an infinite class of models (for example, for simplicity, indexed by a ...
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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
37 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
15 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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29 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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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
40 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
33 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
22 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 ...
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19 views

Accuracy of classification vs. accuracy of class probabilities

I have a dataset that contains a binary response variable: equal to 1 if the person responded to the survey and 0 otherwise, as well as a host of auxiliary variables X. What I want to do is use this ...
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1answer
46 views

What is the best way to represent uncertainty from linear interpolation?

A little background to this question: Part of my job is to conduct flood risk appraisals to help determine the viability of flood defence construction. There is a standardised way to do this, which ...
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0answers
38 views

Correct R formula syntax for lm (or manyglm) for a hierachial experimental design

I have an experimental data set where there are a 16 fish in 4 tanks (64 fish). There are two treatments - Heated and Control and four tanks. Heated was done in tank 1 and 2 whilst Control in Tank 3 ...
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27 views

How to estimate the uncertainty of a function that has to be solved numerically

Consider I have a function: $PV_m^3 - PbV_m^2 +aV_m+ab=RT$ In this example I have measured the uncertainties in $P$ and $T$ experimentally and the errors in $a$ and $b$ can be assumed to be zero. ...
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3answers
61 views

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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0answers
34 views

Predicting future price in high inflation economies

I am trying to create a machine learning model in a country which has high inflation. With this model, I am trying to predict the price of a second hand car. As my train data, I have second hand car ...
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0answers
20 views

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. ...
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1answer
49 views

Checking error covariances between indicator variables in sem/cfa

I'm learning SEM/CFA, and am currently following Beaujean's (2014) book on using lavaan. In the chapter where he talked about CFA and the number of indicator variables to have to ensure the model ...
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0answers
28 views

How can I “select the proper test sample size” to “achieve the best classification quality”?

Homework disclaimer. We were given 10k rows of sample training data. The task is to train some well-known classifiers (as listed below), test their performance and estimate the expected ...
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error in information theory

At the risk of sounding vague, someone told me that errors in information theory usually comes in the form of $c/t$, $c/t^{\alpha}$, or $\exp{(-\alpha t)}$, where $t$ is the $t-$ (or $x$ axis). I ...
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27 views

Estimate prediction error

I actually have a a dataset of 1100 observations containing 99 features and one targeted value (Y). The idea is that my dataset is split in two: 100 observations where the targeted value is know and ...
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1answer
34 views

Do error bars give information about the dispersion of the raw data from the study?

Do error bars give information about the dispersion of the raw data from the study? If data in a graph has standard error bars will this provide information about the dispersion of the raw data ...
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1answer
101 views

Error when using vif() on glmmTMB obejct

I have run a zero-inflated model as follows: number of birds ~ treatment * date + minutes after sunrise + snow cover + (1|site) This was the code: ...
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17 views

Error/Confidence Interval estimation on very specific problem

I'm developing a method which estimates a value $t$ for a very specific problem. Assume that we have an individual $s$ with its associated data but where $t$ is not precisely known and a reference ...
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Decide inventory to carry based on forecast model to max. profit

This is statistical modeling / forecasting optimization question. I have a forecast model which predicts units value for a year. Now if I carry more inventory than prediction, I lose all the extra ...
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1answer
75 views

True or false? (Ridge regression has higher error rate than standard linear regression for test set)

When using ridge regression, we would expect the error/loss function on the test set to be higher than if we used standard linear regression with no penalty. I know that for the training set, the ...
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1answer
27 views

The covariance of 2 independent and identically distributed

I am currently researching a paper and they have the following set-up: " $(\epsilon_{1}, \epsilon_{2})iid \sim N(\mu, \xi)$. captures the collective biases that in-vestors may have about d, is ...
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25 views

Covariances and correlations in curve fitting

I have a set of data that I am trying to curve fit and I'm ultimately interested in the errors on my fit coefficients. I take my errors on each fit coefficient as the on-diagonal elements of the ...
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0answers
21 views

Should the reduced chi-sq of a fit to some points be the same as the reduced chi-sq of a fit through a weighted average of those points?

I have nine data points with three of them taken at x = 2, three taken at x = 4, and three more taken at x = 6. I came up with a straight-line fit for these points, and found the reduced chi-sq of ...
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1answer
51 views

What's the term used when identical feature vectors map to different target variables?

Context: Fitting a Machine Learning Algorithm on a labeled dataset. For a feature vector [a,b,c] and a labeled output/target variable, what's the term used when identical feature vectors map to two (...
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24 views

Past observations & Error terms in GARCH and ARMA models

I am a bit confused concerning some of the "underlying concepts" of ARMA & GARCH models. I know that ARMA models are meant to forecast the conditional mean of a process, while GARCH models are ...
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0answers
11 views

Distance from expected error versus distance from expectation

Model 1: percentage from expectation We have a time series forecasting model that makes predictions every 15 minutes. As a first stab, we classified all those points that were 50% larger than our ...
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5answers
2k views

Why Normality assumption in linear regression

My question is very simple: why we choose normal as the distribution that error term follows in the assumption of linear regression? Why we don't choose others like uniform, t or whatever?
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0answers
25 views

80-20 better than full dataset for LightGBM

Recently I have been using LightGBM as regressor in order to predict, on a dataset of 20 thousand observations. I have two modes, 1) Production and 2) Testing. The first one just trains a model with ...
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1answer
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Determining error between two surfaces given same discrete inputs?

Apologies if this isnt the best SE forum to ask on, but it seems relevant here. I have, as an output of a machine learning algorithm, a surface in z, which has known increments along x and y. These ...
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32 views

Represent Mean-Squared-Prediction error as function of covariance (or Fisher) matrix

Given a simple linear model: $$ y_i = x_i^T \beta + \epsilon_i $$ For simplicity, $\epsilon_i$ is Gaussian iid with variance $\sigma_e^2$, then the solution for $\hat{\beta}$ is given via Ordinary ...
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0answers
13 views

Rank error metric for time series

Suppose I have a collection of MAE across multiple time series (say, 10), and 3 models. However, MAE cannot be compared across time series. I compare the errors in this way: assign ranks to models, ...
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0answers
27 views

Uncertainty from equation involving fitted parameters [closed]

I want to estimate the uncertainty of a calculation which involves a quantity from a fitted mathematical model. More specifically, the end calculation would be something like: P = x / A_tot where I ...