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15 views

Forecasting the business cycle?

I am wondering what is the best way to forecast the business cycle based on the past. Currently I feed the seasonally-adjusted GDP index data to a Hodrick–Prescott filter, extract the cyclical ...
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0answers
25 views

How can I smooth a set of discrete data points for the purpose of schedule planning?

Disclaimer: I do not have a background in statistics or the math behind filtering, save one long-time-ago college course. I have a well defined problem space. I am calculating hourly staffing ...
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1answer
41 views

What statistical method to correct systematic error in the output of a economic optimization model?

I am working with an economic optimization model which attempts to model the dynamics of a certain commodity market (prices, quantities, production etc.) for different frequencies (monthly, quarterly, ...
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1answer
71 views

Filtering using a SARIMA model in R

I am not an expert in statistics, but I would like to work on a SARIMAX model representing power consumption. The exogeneous variable would be the temperature, but for now I found here I might need to ...
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1answer
19 views

Matrix Factorization Recommendation Systems with Only “Like Ratings”

I'm trying to build a recommendation system, but I only have data on what my user's have "liked" i.e. all non-missing data has the same numeric value. Is it possible for me to using matrix ...
0
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1answer
32 views

Heteroscedasticity filter for time series

I am looking for a method or package in R that can remove heteroscedasticity from time series. Specifically, I have a number of time series to which I want to fit a VAR model. Each time series may or ...
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0answers
20 views

Filter algorithm for a system

I have a system with the following structure: $X_{t+1} = X_t + E_{t+1}$ $E_{t+1} \sim N(0, \Sigma)$ $Y_{t+1} = f(X_{t+1})$ $Y_{t+1} \sim {\rm Uniform}(a_{t+1}, b_{t+1})$ So $X$ is a vector of ...
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0answers
27 views

Are trend/cycle filters intended to be used in predictive models, or just analysis?

I am relatively new to time series modelling and for a task I have I've had good success (in terms of forecast error) by first splitting the data into a trend and cycle components using a ...
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1answer
54 views

What does “AR(p) filtered series” mean?

I guess this means that omitting some variables in a certain interval, say, $(x_1, x_2, x_3, x_4, x_5) \to (x_1, x_5)$ in AR(4) model. Is it right? Or does this means eliminating autocorrelations ...
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0answers
7 views

Determining the quality of low-pass filter estimate

I'm taking a low-pass filter, specifically an exponential moving average, of samples coming in every second. Those samples are of electric field strength, and suffer sizable noise. How can I ...
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2answers
53 views

Does filtering of data by effect size violate some assumption of P value adjustment methods?

I have pre- and post-treatment continuous data for a large number of variables that I am analyzing for treatment effect. Normally I would obtain the P values and then adjust them for multiple testing ...
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1answer
73 views

Content-control (web filtering) using machine learning

I'm trying to build a content-control (web filtering) application using machine learning (just for training purposes). For example define gaming sites. I'm somewhat familiar with machine learning ...
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1answer
98 views

What is a density function?

I know about histograms and also know that if we connect the mid-points on the top of bars in a histogram we will get a frequency polygon. This polygon could then be 'smoothed' in a way that it ...
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0answers
47 views

Feature Selection: markov blanket filter

I need to do a markov blanket filter for feature selection for highly unbalanced datasets. There are popular algorithms to do this? I need to understand the algorithm behind this. From what I ...
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0answers
50 views

Filtering with HMM

I want to use HMM for filtering, i.e. to find $p(x_t|y_{1:t})$. I see that the forward algorithm calculates the forward variable as a joint probability; $\alpha_t(i) = p(y_{1:t},x_t=S_i|\lambda)$, ...
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0answers
39 views

Hidden Markov Model: Average steps needed for the filtering density to reach a certain value

I need a hint for solving the following problem. The movement of a certain robot is modeled with a HMM. The robot moves on a circular path and at every time step, it either stays in the same location ...
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0answers
26 views

filtering discrete data

I looking for good ways to estimate a true state of the system from a set of observations, that take several integer values. E.g. I have an sequence of observations X_i of the unknown variable Y. Both ...
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1answer
161 views

Moving average filter for outlier removal

I am using a moving average filter to smooth data for outlier removal. By changing the number of average points, I am getting different result. My data are multi-dimensional feature vectors. I ...
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0answers
138 views

Band pass filter giving ‘wrong’ turning point

I am trying to run a Christiano FitzGerald band pass filter to estimate a long-run trend (with period in excess of 70 years). My data are the demeaned natural log of a commodity price index. My ...
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0answers
71 views

How to extract uniform noise from the mixture distribution

Let $X$ be a sample from the distribution which is the mixture of the useful signal with the distribution $\xi(\theta)$ and a uniform noise $U[a, b]$. The probability of observing $U[a, b]$, the ...
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1answer
217 views

Weka batch filtering on random projection

I am new to Weka. I have used the following statement in Weka CLI: ...
1
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0answers
35 views

What is the difference between a one-sided filter and a two-sided filter when looking at time series analysis?

I'm looking to understand the difference between the two and grasp in which situations each might be preferred over the other.
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2answers
123 views

Smoothing algorithm for saturating function

I have a noisy readout of a curve that is monotonically increasing or decreasing for a narrow range of points and then quickly saturates. I don't know exactly where the saturation point is, but from ...
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2answers
65 views

Method to remove bad values in time series (bad values known to take on a particular value)

This sounds easy, but I don't know of a good statistical method for it. I have a time series that has (good) data points that range from ~3.5 to 30. The data are collected by an automated sensor. ...
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1answer
124 views

Non-causal of variable threshold algorithm

I'm not entirely sure this question belongs here. (Maybe better suited on stackoverflow or theoretical computer science). But here it goes. I'm reading a paper called. "Time-Frequency Analysis of ...
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0answers
48 views

Removing data above the mean

I am working with a data set, for which to remove noisy data I take the average of the sample itself and cut anything above that average. What I'm trying to understand here is does this have a name ...
1
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1answer
377 views

Multivariate exponential smoothing and Kalman filter equivalence

Suppose the time-series $X$ is hidden state Gaussian random walk and we observe $Y = X + e$, where $e$ is gaussian white noise independent of $X$. The Kalman estimator of $X$ in this case has a ...
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0answers
49 views

Question about asymptotics of steepest descent method in the context of adaptive filtering

The model which will be used is defined as $e(n) = d(n) - y(n)$ with $y(n) = x(n)^Tw(n)$. where $e(n)$ is the error term of the n-th observation, $x(n)$ the input vector of the n-th ...
2
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1answer
581 views

State Space formulation of Hodrick-Prescott filter

I would like to apply the Kalman filter in order to get a causal Hodrick-Prescott filter. The Hodrick-Prescott filter models a time series $(y_t)_{t=0}^T$ as $$ y_t = \tau_t + c_t $$ where $\tau_t$ is ...
1
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1answer
851 views

Formula for one-sided Hodrick-Prescott filter

I am not very familiar with filters. The Hodrick-Prescott filter as one can find it e.g. in wikipedia is two-sided. I also found an R implementation for this in the R package mFilter. There the filter ...
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0answers
132 views

MSE of filtered noisy signal - Derivation

I'm working on understanding the derivation of the optimal time constant for filters based on minimizing mean squared error. Unfortunately the text made a big jump between steps and lost me. Here's ...
3
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2answers
875 views

Filtering using ARMA model in R

I have two time-series, x and y. I would like to prewhiten x by fitting an ARMA(p,q) (or in ...
1
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0answers
32 views

Filtering virtual economy transactions

I am currently writing a pet-project for a browser based game which consists of two parts, first part is a data miner which observes the transactions in the market. And second part is as you might ...
5
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1answer
224 views

Determining smoothing parameter in HP filter for hourly data

I'm trying to determine a smoothing parameter for the Hodrick-Prescott filter. I've seen that there are papers on the topic but they are far too advanced for my comprehension. If I have a data set, ...
3
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1answer
78 views

Distinguishing statistical (global) and network (local) effects

I am analyzing how users of specific service affect each other by observing communication between them and changes in membership plans. The social network consists of 3M users and 40M connections ...