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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How to find percent of error? [closed]

I set the temperature of system as max-min at 14-17 degree celsius. and the collected data from system as follows. 14.9 20.1 16.7 16.2 16.1 17.8 18.7 19.4 17.2 15.8 15.4 15 14.8 14.5 14.6 14.6 14.6 14....
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Understanding error in bayesian inference

Let us say we have: Data $X$ Parameter that we are trying to estimate is $\Theta$ The Bayesian estimation method is to Assume a prior on $\Theta$ Sample $x$ from $X$ Use Bayes theorem. Compute the ...
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What are some good relative regression metrics?

Which relative regression metrics exist? What are their strengths and weaknesses? In what case do you use each? --> Bonus point if they are already/easily implemented in Scikit-Learn. I have a ...
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Given a particular target imbalance, how can we predict the macro precision and recall of a model trained on random normal data?

The micro precision of a random classifier, give a positive class probability of p, should be p/p+N where N is the number of samples. And the micro recall should just be p. To test this, I generated a ...
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How do measurement errors propagate into Percentiles?

I have a measurement systems that outputs $X_i + dX_i$ measurements. I'm trying to figure out the most correct way of estimating quality of measured device. The relative error $dX_i/X_i$ is normally ...
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ARPACK error 3: Unable to compute the largest eigenvalue using eigs from scipy.sparse.linalg [closed]

I am tryring to compute the largest eigenvalue using eigs from scipy.sparse.linalg for the matrix L (204 x 204) with the same values given below. 1 on diagonal and -0.004901961 on off diagonal. $ L = \...
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What is the distribution of the error term in the Poisson Regression model? [duplicate]

Given a Poisson regression model as $y = E(y\mid x) + ε$ where $λ = E(y\mid x) = \exp(x'β)$ with $y$ from the Poisson distribution ($\operatorname{Poisson}(λ)$) I am trying to understand the ...
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Error bars on error bars?

Inspired by my recent attendance at an environmental toxicology conference, I have the following question about error bars: Let's say that I'm drawing samples from some unknown distribution, with ...
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Is there a clear interpretation of Corr(X, X+Y) in research?

Consider a case of $Corr(X,Z)$, often found to be high; where later, it was found that it holds exactly $Z = X + Y$. In effect, the previously found correlations were equal to $Corr(X, X+Y)$. How can ...
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Why not use exact probability in 0.632 or 0.632+ method with small sample size?

The .632 estimator (and extensions like .632+) developed by Bradley Efron are founded on the following premise. Suppose we have a data set with $n$ observations, and we draw $B$ nonparametric ...
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frobenius norm and missing data

I'm calculating the frobenius norm on the differences between two matrices (so that I can minimize the result to reduce error). However, one of my initial matrices, and thus the difference matrix, ...
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Mean squared error of 2 distributions when there are many zero values

I am comparing two (2-D) distributions using mean squared error. I take the difference between distributions, square them, average them and multiply them by the area of a pixel/bin. These ...
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Estimate errors of predictions of a model based on its metrics

I have trained a classifier with some data and I was able to get, let's say, for two classes C1 and C2 a recall of R1=0.71$\pm$0.06 and R2=0.94$\pm$0.02 (with the errors originating from a repeated K-...
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What is the 1 standard deviation error in papers

I have recently come across some papers in my field. They had a large (X,Y) data set, it was binned into 4 bins. Least square method was used to find slope (m) and y intercept (b). In the table that ...
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Error Terms in the ANOVA Summary Table

my lecturers require us to write the error term for the effect/source in the ANOVA summary table. Such as below: I don't understand how to find which S(error) term goes to which source. And I do know ...
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SE Interpretation

Can you help me to interpret the following standard deviation? It is a linear regression problem, I need to predict Rent which depends on the size of an Apartment. Rent=23.411+13.806. The question is ...
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Trying to understand the math behind Avi Wigderson's simple example

In his celebrated talk on randomness and pseudorandomness https://youtu.be/Jz1UoAWD80Q?t=366 legendary mathematician Avi Wigderson makes the powerful statement that sampling is perhaps the most ...
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How can I estimate the variance of the error terms in a conditional/multinomial logit model?

Conditional/multinomial logit models(CML) can be esimated by the Maximum Likelihood Estimation(MLE). The likelihood would consists of choice probabilities: \begin{equation} P_{ij}=\frac{e^{V_{ij}}}...
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How to calculate error for data that changes as a function of time

I have a set of data that I would like to calculate an error for. The data is an electrical current from an electrochemical experiment, recorded as a function of time. As the experiment proceeds, the ...
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Estimation of standard error in observables generated from time series data

Imagine that I have time series data which are time-correlated, non-scalar, and of unknown, but identical distribution From this time series I have a function that takes an subset of X as input to ...
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Residual of marginal effects

I am trying to understand how marginal effects works. If i have calculated Marginal effects of a logit model, does some type of unit error exist? I don't know if this is a correct term, but an error ...
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Distribution of the approximation error in Gaussian Process Regression (finite data setting)

I am learning about Gaussian Process Regression. I would like to have some references or results regarding the distribution of the error between a given function, and the posterior obtained in ...
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How to approximate MAE of monthly values from MAE of daily values?

Suppose I have the Mean Absolute Error (MAE) of daily values for a period of, say, 1 year. Assume the errors are normally distributed. The value for a month is equal to the sum of the values for each ...
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Covariance matrix of errors for homoskedasticity/heteroskedasticity

I've seen homoskedasticty and heteroskedasticity defined as the following The error term of our regression model is homoskedastic if the variance of the conditional distribution of $u_{i}$ given $X_{...
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MAPE does not take into account the range of the output?

I have a time-series regression model where the output is always in the range of 6000-6050. After training my model, I get a Mean Absolute Error of around 18 and hence, very low Mean Absolute ...
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Variance of random walks in time series analysis [duplicate]

“For a random walk stochastic process, the variance is infinite.” Do you agree? Why?
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special form of a paired design (very small, unbalaned)

I am trying to figure out how to analyze following design. Suppose three samples are taken from the starting material of an experiment which will be performed at larger scale (LS). The same ...
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Metric that quantifies 0-centered error throughout the entire range of the data?

Say I am selecting between models, and I especially value mean-0 error throughout the entire range of the data. I am looking for metrics that specifically capture this property. For example, take the ...
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Estimate of an observable and its uncertainty from two inconsistent measurments

Suppose two independent experiments are set up to measure the same observable $\mathcal{O}$ in the same way and report two results $$ o_1 \pm \delta o_1^{stat}\pm \delta o_1^{sys}, \quad \quad o_2 \pm ...
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Scale-independent error metric for data with many zeros

I've been working on a time series forecasting model. I can't use a scale-dependent error measurement. And my target outputs also occasionally have zeros, meaning I can't use MAPE either. What is the ...
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Meta analysis average percentage difference with standard error

I am collecting data on the effect calorie labeling has. Each study provides a value for mean calories consumed before the calorie label and after. Each number has a standard error or deviation ...
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If the error terms in a regression setting are not observed, how can we ensure they're normally distributed?

According to the G-M assumptions, we should assume spherical errors. But my understanding is the errors -- as measured by the vertical distance from the true line of best fit to the response ...
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incorporating error in best fit line equation

I have two sets of data {X} and {Y} each element in those two sets has its own unique +/- error. I graphed x vs y in a scatter plot along with every point's error bar (both in x and y (x1 +/- a1 , y1 +...
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What order of power mean best estimates the median of a gamma distribution?

Suppose we have a gamma-distributed random variable $X$ whose shape/scale parameters are known to be $\alpha$ and $\beta$. What order $p$ for the sample power mean $\hat M_p[X]$ minimizes $$ (\mathcal{...
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Taking the logarithm of observational errors

I have a set of observational measurements, each with their unique +/- observational error. I need to take the logarithm of this set of data. My question is, to include the error bars in the logarithm ...
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Equal Error Rate in Hidden Markov Models for Speaker Recognition

I was asked to report the Equal Error Rate (EER) for my speaker recognition proposal. I trained one HMM for each speaker. To evaluate, I introduce the input of an speaker in both models and classify ...
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Error on X having Y(X) greater equal to some constant A

There is a variable $Y(X)$ as a monotone increasing function of $X$, and there is an error data of $Y$. I want to find the minimum $X$, satisfying $Y(X)\geq A$. What will be the error on $X$ in this ...
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How can I minimize forecasting error in 100 probably correlated time series data streams with incomplete data from each one?

Suppose that I have 100 restaurants with identical menus and ingredients they need to procure to stay in business. Let’s assume that they have 100 menu items per restaurant and 500 ingredients in ...
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Mean of Relative Error Vs. Coefficient of Determination

Consider we have a method that estimates a specific parameter. We want to find the accuracy of this method and we have 10 samples (these samples include the true values of the parameters and their ...
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Is it wrong to run a Random Forest on high-dimensional, sparse, and unbalanced data?

I am learning about random forests, and I have been testing using R. I have doubts about whether I am doing something wrong given that my data are: sparse, high-dimensional, and unbalanced. Trying to ...
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Standard Error on the Mean for Asymmetric Distributions

Gaussian - symmetric case: consider a statistically independent sample of N observations from a normal distribution.The mean (loc) of the population is the results on which you would like to make a ...
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How do I calculate $\sigma^2$ within the $\varepsilon = N(0, \sigma^2)$ notation

The error term for an AR(1) model is assumed to be $\varepsilon = N(0, \sigma^2)$, a mean of 0. An example of a source that mentions this: The AR(1) model can be written in intercept form, $$z_t = \...
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Representation of error values for large and small raw values

Assume a population where the numbers are in the range of [0:200]. Assuming the numbers represent the performance of a program, e.g. seconds, the numbers look like ...
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Why multiple testing matters?

I am learning multiple testing and I am curious about why it matters? I understand the mathematics behind the multiple testing problems, for example, I understand things like $\text{FWER} \le m \alpha$...
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How can I find the percentage accuracy between an approximation and a source formula?

Im trying to find the percentage of error for a trigonometric sine graph. I wrote an approximation of the graph, and am comparing the two up close, https://www.shadertoy.com/view/NslfRs Red represents ...
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Probability of a discrete variable depending on continuous variables

I have one random variable : $Y$ and a set of three parameters $\vec{X}=(X_1,X_2,X_3)$. The variable $Y$ is discrete. I don't know its distribution and I am trying to extract it from data. I am doing ...
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Why doesn't mean square error work in case of angular data?

Suppose, the following are the first few lines from a dataset for solving a regression problem: ...
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type 1 error and size of the test

In a lecture that I am attending, the lecturer refers to type I error probability $\alpha$ as "the size of the test" and $1-\beta$ as "power of the test". I have an intuition for ...
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3 votes
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Alternative to mean absolute percentage error (MAPE)

MAPE metric has problems when the actual value to be predicted is very small. In the extreme when the actual value is 0 then MAPE will be infinity (if the prediction is not exactly 0). What about this ...
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How could an oracle that knows the true distribution of things would still incur some errors?

The ideal model is an oracle that simply knows the true probability distribution that generates the data. Even such a model will still incur some error on many problems, because there may still be ...
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