Questions on (linear or nonlinear) regression, the fitting of functions that best approximate empirical data.

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4
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153 views

How to compare the similarity between functions?

I'm designing a web service that finds the regression function of a pattern within an image. I analyzed three images and found the following three regressions: 1) $f(x) = 74.7602 + 0.2005x - ...
3
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33 views

Bayesian linear regression cost function

I am studying classification using linear regression . Now, I want to map it in Bayesian regression. Let talk about binary classification using linear regression again. Assume that I have a set ...
3
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51 views

Determine whether ARMA(p,q) is stationary and/or invertible?

Determine whether an ARMA(p,q) process is stationary and invertible such that $y_t = \sum_{i=1}^{p} \phi_i y_{t-i} + \sum_{i=1}^{p} \theta_{i} \epsilon_{t-i}$ with the restriction that ...
3
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0answers
103 views

Can the sigmoid function approximate any function (or relation) where 0<y<1

I'm studying Machine Learning and Artificial Neural Networks. Some basic principles of Machine Learning are linear regression, multivariate linear regression, and nonlinear regression. The last of ...
3
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0answers
113 views

Multilinear or Tensor Regression?

Given input data $x_t\in \mathbb{R}^n$ and output data $y_t\in\mathbb{R}^m$, the closed form solution to $\min_A \sum_t \|y_t - Ax_t\|^2_2$ is given by $A = (XX^T)^{-1}XY^T$ where $x_t$ form the ...
3
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0answers
135 views

How to perform nonlinear regression with correlated errors?

I have a nonlinear least squares problem, but the errors are correlated. I could use R's nls function to do the regression if the errors were independent, but I don't know the right way to handle ...
3
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0answers
259 views

Least Square Method with Positive Parameters

this is my first post here in the Stack Exchange. A friend told me about this forum and I'm giving it a try. I searched a bit past threads, but couldn't find what I wanted, so I'm posting the problem ...
3
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830 views

Correlation and Regression Question

Two separate tests are designed to measure a students ability to solve problems. Several students are randomly selected to take both tests and the results are: $$ \begin{matrix} \text{Test A}(x) ...
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10 views

Showing Hat matrix equal specific values

Consider a one way layout model $y_{ij}$ = $\mu_i + e_{ij}$ (1 $\leq$ i $\leq$ a, 1 $\leq$ j $\leq$ $n_i$) where a = 3 and $n_1$ = 2, $n_2$ = 3, $n_3$ = 4. Show that the hat matrix for this design ...
2
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94 views

Is it compulsory to make transformation to the econometric model in order to have only diagonal elements on variance-covariance matrix of errors?

I need some sharped and advanced advices for the following issue ... Model and its assumptions I'm working on the methodology of a two-way error component model. Here is the model: $y_{jis} = ...
2
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0answers
29 views

What is ${\rm cov}(e_i, \hat y_i)$ in simple linear regression?

The model is $y_i = \beta_0 + \beta_1x_i + \epsilon_i$ What is ${\rm cov}(e_i, \hat y_i)$? What is ${\rm cov}(\epsilon_i, \hat \beta_1)$? What is ${\rm cov}(e_i, \epsilon_i)$? For 1, I am writing ...
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31 views

Smallest set of Liner equations, which exactly fit a set of points

I have a set of 2-d points,(it can be of any arbitrary dimension n). I want to find the minimum set of straight lines(linear equations) which exactly passes through the given 2-d points (unlike ...
2
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0answers
42 views

Computing evidence for least-squares fit

I'm at a loss trying to implement Bayesian model selection for standard least-squares polynomials fits. I have three polynomials of order $1$, $2$, and $3$, and a sequence of $(x,y)$ data points. ...
2
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0answers
36 views

Coefficient of determination

$$ \displaystyle \sum^n_{i = 1} (y_i - \bar{y})^2 = ( \displaystyle \sum^n_{i = 1} (y_i - \bar{y})^2 - \displaystyle \sum^n_{i = 1} (y_i - \hat{y}_i)^2 ) + \displaystyle \sum^n_{i = 1} (y_i - ...
2
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0answers
118 views

Minimizing L4/ L6/ L2N norm for linear regression

OLS regression minimizes the sum of the squared errors. The normal equation for an OLS for $L_2$ minimization is as follows: $$b= (A'A)^{-1}A'y$$ What would be the equation to minimize the $L_4$ norm ...
2
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124 views

Orthonormal Matrix weighted regression

$Q$ is a rectangular matrix with orthonormal columns. A linear system composed of $$Qx= b$$ is really easy to solve as: $$Q'Q=I$$ hence: $$x=Q'b$$ Given that $Q$ is orthonormal can this be used to ...
2
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0answers
82 views

Regressing $Y$ back on the residuals

Suppose I have the linear regression model $ \hat{y_i} = a + b x_i $ for $a,b$ obtained via OLS. How does one regress $y$ back on the residuals $\hat{e}_i = y_i - \hat{y}_i$? If we write $ ...
2
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0answers
128 views

Effective model for calculating momentum or growth rate for a time series

I have a series of numbers tracking the performance of an entity on any given day. It's nothing but a simple integer for each date. For example, here's a series for Entity "X" ...
2
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0answers
239 views

Bare minimum of points in multiple polynomial regression

I have a question on multiple polynomial regression and the absolute minimum amount of points in the different terms. The minimum amount of points required for a second order polynomial would (in one ...
2
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0answers
83 views

Find $w$ as the minimizer of regularized logistic regression

Could someone point me to a reference on how to find $w$ as the minimizer of: $$ \frac{1}{2}\sum_{i=1}^{d}q_i(w_i-m_i)^2+\sum_{j=1}^{n}log(1+\exp(-y_jw^Tx_j)) $$ where $q_i$ (initialized with ...
2
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0answers
331 views

Logistic regression algorithm in Casio and Texas Instruments calculators

When using logistic regression on a Casio or Texas Instruments calculator, the output is of the form $$f(x) = \frac{c}{1+ae^{-bx}} $$ The problem I have (when teaching in a class where both types of ...
2
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0answers
287 views

Finding a model for multiple non-linear regression

I want to implement a regression analysis, but I have problems with finding a model for the given data. There are $149$ $(x,y,z)$-values. $y$ values are all positive, $x$ is between $[-10, 10]$ and ...
2
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0answers
2k views

Derivation of standard error of beta in simple linear regression

Countless web pages show the equation for the standard error of the slope in a simple linear regression. For example: ...
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0answers
2k views

Help with problem: Estimated Standard Deviation of Regression Equation (Simple Linear)

This is a practice problem. I've solved part (a). I have provided verified answers (from the published key) to all parts (a), (b) and & (c). I need help solving (b) and (c). Consider a simple ...
2
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0answers
241 views

Surface Function Fitting to Spherical Data

I have a set of geographic (longitude,latitude,value) data to which I would like to fit surface functions, specifically, the set of quadratic surfaces: $f(x,y)=Ax^2+Bx^2+Cxy+Dx+Ey+F$ At the moment, ...
2
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0answers
64 views

Accurate computation for Linear Regression case

I am writing a program that inputs a sequence of points $(x_i,y_i)$ based on the user clicking on certain pixels in an image shown. The program should then find the "best -fitting" line in the least ...
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12 views

Non-Linear Regression involving the maximum function

How do you calculate the regression of this model? I know Minitab and MATLAB, so if you guide me with these software I would totally appreciate it. $$Y=c+\max(X^{-n}, 0.34) $$ Here c and n are ...
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14 views

Good MSE doesnt imply good prediction in logistic regression?

I am writing some code for regularized logistic regression. I observe this interesting phenomena and wonder if it is a normal thing or just my code is wrong. For loss function, I am using the ...
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0answers
19 views

Deriving cost function using MLE :Why use log function?

I am learning machine learning from Andrew Ng's open-class notes and coursera.org. I am trying to understand how the cost function for the logistic regression is derived. I will start with the cost ...
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8 views

Finding posterior of normal distributions and logistic regression.

$P(w_0 | x) = \frac{1}{1 + e^{-log\frac{P(x|w_0)}{P(x|w_1)}-log\frac{P(w_0)}{P(w_1)}}}$ Note: x = $[x_1, \dots, x_d]^T$; a $d$ dimensional vector. $w$ can take on one of two values: $w_0$ or $w_1$. ...
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0answers
20 views

How to represent the parameters in logistic function

I want to find the parameters in logistic function. I read the guide at here. It very clear to explain. But it did not has final solution that I need. Now, we will consider a basis logistic function ...
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0answers
27 views

Properties of best linear predictor?

Conside two scalar random variables, $Y,X$. The best linear predictor of $Y\mid X$ under square loss function is $\theta_0=\operatorname{argmin}_{\theta} ...
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29 views

How does Linear Regression classification work?

I am currently trying to understand the following: Logistic regression is a probabilistic, linear classifier. It is parametrized by a weight matrix $W$ and a bias vector $b$. Classification is ...
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0answers
11 views

Proofs on regression analysis

How can I prove: 1) estimating population variance $\hat\sigma^2={1 \over n-2}[S_{YY}-{S^2_{XY} \over S_{XX}}]$. 2)expected value of error mean square=$E(EMS)=\sigma^2$ To prove (2): I showed that ...
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0answers
19 views

Problem on Linear Regression

Consider the following 2-variable linear regression where the error $e_i$ 's are independently and identically distributed with mean 0 and variance 1; $y_i = α + β(x_i − \bar x) + e_i , i = ...
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26 views

Multinomial Logistic Regression

(1) $$P(y^{(i)} =1\mid X,W) = \frac{\exp(W^{(i)^T}X)}{\sum_{j=1}^m \exp(W^{(j)^T}X)}$$ $W$ and $y$ are vectors where the superscript is an index. And there are $m$ classes (that is, there are $m$ ...
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0answers
14 views

General 2D taylor surfaces from axial behaviour and discrete points

I have a problem as follows: I have a nonlinear function, f(x,y), for which I (numerically) know the axial behaviours, f(x,y0) and f(x0,y), where x0 and y0 are constants. I can calculate discrete ...
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0answers
18 views

Predicting y from a log-linear regression

I was wondering if someone could explain to me the very last step on the right hand slide. Why is do we have a sum rather than a product. Thank you very much.
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0answers
20 views

Logistic regression eye treacting data (need model)

I have two sets of time course data, they are for an eye-tracking study. The data is 20 100ms chunks, one category being percent fixations for canonical sentences, and the other being percent looks ...
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0answers
16 views

Regression factors and covariance matrix

I am trying to follow some notes. They have two matrices. One is called comfact (company factors). This is a $580 \times 5$ matrix. The $580$ rows represent $580$ different companies. The $5$ ...
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0answers
36 views

Linear Regression Question (Linear Algebra) Help!!

Hey guys, I have a quick question. I am trying to prove that the squared sample correlation between fitted and observed values is equal to $R^2$ (coefficient of determination). I am having a lot of ...
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0answers
25 views

How to find a function that can approximate another blackbox function programmaticly?

This question has been posted on http://stackoverflow.com/questions/21758016/how-to-find-a-function-that-can-approximate-another-blackbox-function-programmat I was suggested to post it here. I ...
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0answers
20 views

What is correlated with what in a linear regression?

I'm trying to make sure I understand the ins and outs of a linear regression and am making a table for what is correlated with what, so just want to see if I have everything included. I'm looking at ...
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0answers
38 views

Solving a linear matrix equation with respect to the maximum of the euclidian distances between rows.

With $n>m$, real number matrices $A$, $B$, $C$ are shaped like: $$A=\left( \begin{array}{ccc} a_{1,1} & \cdots & a_{1,m} \\ \vdots & \ddots & \vdots \\ a_{n,m} & \cdots ...
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27 views

Adjusting regression for small sample bias

I have a set of data points $\{x_i\}$. These data points are grouped so that (say) $i\in\{1,2,3\}$ is group $A$, $i\in\{4,5,6,7\}$ is group $B$, etc. I would like to test the null hypothesis of no ...
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0answers
26 views

Polynomial regression - differences between algorithms

I know that I can find a polynomial regression's coefficients doing $(X'X)^{-1}X'y$ (where $X'$ is the transpose). This is a way of finding them; now, there is (as far as I know) at least one other ...
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0answers
36 views

Linear Regression with multiple equations

I am trying to implement a linear regression algorithm to fit a set of "true" points with their "observed" location. The points are specified using spherical coordinates on a unit sphere. I have a ...
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0answers
2k views

Linear regression: degrees of freedom of SST, SSR, and RSS

I'm trying to understand the concept of degrees of freedom in the specific case of the three quantities involved in a linear regression solution, i.e. $SST=SSR+SSE, $ i.e. Total sum of squares = ...
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140 views

Formulize / eureqa any replacements?

Greets Now that Formulize / Eureqa now charge $30.00 a month for use and have crippled the trial version does anyone know of any replacements that can do similar things like find an equation given ...
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0answers
43 views

Linear Regression with limited information

You have grades ($Y $) for men ($D = 0$) and women ($D = 1$). The mean grades (out of total possible score of 100) are 65 for men and 72 for women. Regression of $Y$ on $D$ yields: $Y_i = b_0 + ...