# Questions tagged [parameter-estimation]

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### What is the best way to model survival when the hazard rate decreases over time?

The standard survival analysis model - for example the model which forms the basis for the proportional hazards model - assumes the hazard rate is constant. In many applications this would be the ...
21 views

### predict parameters of linear function

My questions seems very trivial, but I can't quite grasp it. I am also aware this post asks for opinions and knowhow, but do not know were else to ask. I do have quite a lot of experience solving even ...
22 views

### MLE for Poisson conditioned on multivariate Gaussian?

I am writing some Python code to fit 2D Gaussians to fluorescent emitters on a dark background to determine the subpixel-resolution (x, y) position of the fluorescent emitter. The crude, pixel-...
27 views

### Gaussian Mixture Implementation and Optical Recognition of Handwritten Digits Data Set

Trying to implement Gaussian Mixture model implementation in python using the Optical Recognition of Handwritten Digits Data Set which consists of 10 training folds each of size $\left[100x64\right]$, ...
21 views

### How to reverse engineer a logarithmic equation

I am trying to reverse engineer the parameters of a human-designed logarithmic equation. Here are the facts: The equation is of the type a = x * ( y ^ b ) a and b are known, x and y are unknown and ...
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### Mapping 4 Dimensional array to predicted output text

Iv been studying machine learning but im struggling with some concepts and cant seem to find particular answers to the question of how theoretical data is mapped into non classification categories. ...
100 views

### Paramaeter estimation in noisy conditions with Machine Learning, possible?

Let's take two constants, $\alpha$ and $\beta$, both are given by two functions $f_1(\vec{\theta})$ and $f_2(\vec\theta$) (the model). These functions are known: we have an analytical closed ...
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834 views

### Gibbs sampling in R

I have the following model: $y_{it}=\alpha + x'_{it}\beta_{i} + \epsilon_{it}, \text{ } i=1,2,...,N, \text{ } t=1,2,...,T$ (1) $\beta_{i}= z'_{i}\gamma+\eta_{i}$ (2) with \$\epsilon_{it} \sim N(0,\...
190 views

### Artificial Neural Networks and Efficient Parameter Optimization

I have a bunch of test measurements data and a semi-empirical model that has 18 parameters which I have to find so that the model fits my data well. So far I've managed to find and optimise the ...
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### How to Ascertain Sine Wave and Harmonics

I have some data that I've noticed conforms to a sine wave. Details of the data is unknown. My task is to approximate it as closely as possible. From some experimentation in Excel, I noticed the data ...
4k views

### Which one first: algorithm benchmarking, feature selection, parameter tuning?

When trying to do e.g. a classification, my approach currently is to try out various algorithm first and benchmark them perform feature selection on the best algorithm from 1 above tune the ...