Stack Exchange Network

Stack Exchange network consists of 175 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange

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.

1
vote
1answer
8 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 ...
0
votes
1answer
23 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: ...
0
votes
0answers
15 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 ...
0
votes
0answers
11 views

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 ...
-1
votes
1answer
47 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 ...
0
votes
1answer
23 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 ...
0
votes
0answers
13 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 ...
1
vote
0answers
20 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 ...
2
votes
1answer
46 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 (...
0
votes
0answers
20 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 ...
0
votes
0answers
9 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 ...
13
votes
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?
1
vote
0answers
18 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 ...
0
votes
1answer
34 views

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 ...
0
votes
0answers
13 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 ...
1
vote
0answers
11 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, ...
1
vote
0answers
22 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 ...
0
votes
0answers
9 views

division of of values with standard deviations

I need to normalize results from my experiment to the control in that experiment. I have two repeats from each condition (test and control), and each has a standard deviation. When dividing to ...
0
votes
0answers
22 views

Calculating error/confidence interval on points of a distribution

This is a beginners question, coming from an absolute beginner in statistics, but I haven't been able to find anything about this online, probably because I don't even know where to start looking. My ...
24
votes
8answers
4k views

Do error bars on probabilities have any meaning?

People often say some event has a 50-60% chance of happening. Sometimes I will even see people give explicit error bars on probability assignments. Do these statements have any meaning or are they ...
1
vote
0answers
8 views

When making a fit to data without weights, how reliable are the fit errors?

I often need to fit data which is a spectrum. And it isn't possible to have many identical spectrum from which to produce error bars on the individual points in an averaged spectrum. So my question ...
0
votes
1answer
15 views

Decision Tree on a set with reliabilty information

I've got an introductory AI course in my university, and I was taught about decision trees. I'm now facing a classification problem that seems solvable with a DT, but I'm stuck with an unseen ...
1
vote
0answers
25 views

Binomial and Beta-binomial regression error metrics

I have dose-response data where my response is made up of successes and failures (i.e. binomially distributed) with a range of dose values. Typically the relationship between the two is positively ...
0
votes
0answers
13 views

definition of integrated- and- exponential autocorrelation time

I understand them (to an extent) both seperately, but i was reviewing my notes from class and my verbal definition is effectively stating the same thing in different words. I have: integrated: ...
1
vote
0answers
20 views

What is the center of error ellipse?

Is the center of error ellipse representing true value or observed value?
0
votes
1answer
16 views

How is the error calculated when you have a batch size > 1?

There is nowhere an answer to be found for this. So, when i have a batch size of 1, the network calculates an error and then uses it to backpropagate and adjust weights. But what actually happens ...
1
vote
1answer
74 views

What is the error of my regression? [closed]

I'm conducting a polynomial of a third degree upon a diode measurement where Amplification was measured against Voltage. It's a very exponential behavior. However, I used the ...
2
votes
1answer
40 views

Error of Bias-Corrected Kurtosis Estimators

Background I've found two different bias-corrected estimators for the kurtosis. The first one is used in various software packages, such as MATLAB, and is called bias-corrected in the respective ...
0
votes
1answer
48 views

Why temporarily add 1 to an error when squaring it? [closed]

I'm trying to understand how the optimisation is working in an algorithm. In support of the optimisation, errors are calculated. For one type of error, before it returns the value, it squares the ...
0
votes
1answer
65 views

Derivation of Formula for linear regression with data points forming a circle

Suppose we have one dimensional data with following conditions.1. The value of this single feature lies in the closed interval [-a,a].2. The associated target value with each data also lies in the ...
1
vote
0answers
8 views

Calculating the margin of error on an estimated total number of class instances in population

I have a completely random sample of size 10 from a population of objects (population size 1000, if that helps) which can belong to either one of two classes, A or B. Based on a guess from superficial ...
0
votes
1answer
48 views

Estimating the true error rate from the optimistic resubstitution (or apparent) error rate of a PLS-DA model

In short, I'm trying to calculate the 'Upper bound 3' [Ref, p.4] of the true error rate for my partial least squares regression model (PLS-DA), separating two classes A and B of a sample set. Let me ...
0
votes
0answers
10 views

High error value when estimating model parameters

I have a non linear system of ODEs and to estimate 4 of the model parameters I am using Matlab fmincon by minimising the sum of squared errors (SSE). I have only 5 ...
1
vote
1answer
25 views

How to improve a model that is consistently underestimating

I've been trying to predict house prices (real data from my country) and I noticed that initially, errors are centered around zero, but around the $2,500,000 mark, the model starts underestimating ...
0
votes
0answers
64 views

Base Error Rate

I am working for my final exam and I saw this sample question: Given this dataset, Assume we have the following gender detection problem, given the observed hair length and height (both discrete ...
0
votes
0answers
6 views

Independence and identical distribution of the error observations [duplicate]

if I know that the observation (xi,yi) are i.i.d. this should not imply that the r.v. are independent, indeed there could be some correlation between the same vector of observation i.. so could I ...
1
vote
1answer
105 views

calculating overall error in k-fold cross validation

when using k-fold cross validation i thought the overall error was equal to the mean of errors of each fold. the error being anything from MAE and RMSE to NDCG,F-measure, precision and recall. however ...
1
vote
2answers
37 views

Is the error term a sum of r.v.?

`If in a econometric model I have: $y = \beta x + u$ where u is the error term, we have: $u = y - \beta x$ Supposing that $\beta=1$, $y\sim N(0,1)$, $x \sim N(0,1)$ and $x$, $y$ are independent. ...
1
vote
0answers
57 views

Accounting for errors in independent variable through Gaussian process regression

In Gaussian process regression (GPR), one applies a kernel (i.e. covariance function) to describe the similarity between observed and predicted data in the domain. The diagonal of the covariance ...
0
votes
0answers
18 views

Stationary and ergodic r.v: relation between error and independent variable

In time series often hold the condition that a r.v. is stationary and ergodic, allowing the application of the law of large number. If in a model as: Y= a + bX + u ...
1
vote
0answers
54 views

Independence relation between observation and error [duplicate]

Having a simple model like: Y = a + bX + u where u represent the error term, if I know that the observation of X and Y are i.i.d, also the error term is i.i.d?
0
votes
1answer
15 views

criteria for percent error?

I have 2 arrays. The first array is system rating {69.73, 56.93, 68.64, 65.58, 70.36, 67.44, 56.34, 75.03, 51.58, 65.7} The second array is human rating ...
1
vote
1answer
21 views

Propagation of asymmetric uncertainties

I have two (fully independent) measurements of the same quantity X. Each of them reports a measurement $X_{\sigma_L}^{\sigma_R}$ where $\sigma_L$ and $\sigma_R$ are the left and right uncertainties (...
0
votes
0answers
121 views

weighted kappa for intra/inter-rater reliability in SPSS

I am working with ordinal scales for cerebral atrophy (ratings 0 to 4) and vascular burden (ratings 0 to 3) assessed by two raters. I have installed the extension bundle for weighted kappa from SPSS ...
0
votes
1answer
49 views

Is error function always assumed and convex?

While updating weights of the neural network, most of the algorithms use convex optimisation because of the reason that error is a convex function. My doubt is that whether the convex-ness of error ...
1
vote
1answer
47 views

Why errors are written additively in a regression model?

I was curious about: Why do we write errors (or disturbance term) $\varepsilon$ as a additive term in a regression model? To elaborate, whether we consider a paramteric or non-paramteric regression ...
0
votes
0answers
12 views

Type II error for share price event study - what is the difference between one and several securities?

I have a question regarding the type II error for a specific event study. It is a case study (i.e. one observation) with daily share prices. I want to test whether event day abnormal returns are ...
0
votes
0answers
28 views

Error variance estimation with weights

I am using data which include a (sample-)weight for each observation, i.e. the data is from a survey that has weights to make the sample representative for the US-population. I perform OLS to get some ...
0
votes
0answers
61 views

Correct approach to Mean Absolute Percentage Error

Currently I've been working on sales data. I have different categories that have very different figures (e.g. Groceries vs Technology), so I decided the best approach was the MAPE. The thing is, I ...
0
votes
0answers
19 views

Calculate the Confidence Interval for the Error of Model

I am not sure I am thinking about my problem the right way, so I am looking for the right approach. I have a data set that, for the sake of argument, has a mean of 1 and a standard deviation of $\...