0
votes
0answers
18 views

Fitting ARIMAX with lagged X variable (Matlab)

This question is divided into two parts. I currently have a Y vector with 364 data points (Y) and an exogenous variable (X) with 364 data point. X is a good predictor for Y that I want to pair up ...
0
votes
0answers
15 views

ARIMAX model or ARDL?

I would like to study the impact the advertising of a product on its sales (weekly data for 5 years). As the final aim is to forecast what would be the impact on sales of a change in the advertising ...
3
votes
1answer
27 views

Is there a method to disentangle multiple lines of data that are intermingled?

I have 3 temperature sensors that record data once a minute. All 3 temperatures have the tuple value (instant, temperature). The problem is, they may come in a random order and thus there's no way to ...
2
votes
1answer
26 views

standard errors of the fitted values of a time series regression

I really want to understand how the math is working here. I am trying to get the standard error of the fitted values for a time series regression model.In the non-time series regression,I know I can ...
3
votes
2answers
119 views

How to estimate model with both linear and exponential parameters?

I have a theoretical growth function that can be perturbed by events, and I'd like to estimate the growth parameters as well as the perturbation, and the rate of falloff after that perturbation. I'm ...
4
votes
1answer
58 views

Product price prediction - include important external factors

I need some hint over what is the general prediction solution to modelling products prices in such a case: I have several models (types) of the product I want to predict prices for each of these ...
0
votes
0answers
31 views

Financial time series model

I have an interesting question that I think has not been asked yet here. I am building an AI that has as goal to predict how wrong a standard based-on-history model is. This is done based on Natural ...
0
votes
0answers
12 views

Is time-delay embedding/attractor reconstruction used in some machine learning algorithm?

I try to model/forecast blood glucose levels from my diabetes diary, so I have to deal with some 5-7 daily measurements of estimated carbohydrates, physical activity, insulin doses and measured blood ...
3
votes
1answer
120 views

Doubts in linear regression

If a linear regression model has a constant term say 1 or 0.2, for example if the original model is $y(t) = 0.2 + ay(t-1) $, then what does this constant term imply? Will it hamper the estimates if ...
2
votes
1answer
113 views

Can we skip the lower order terms in interactions? [duplicate]

This question is about three-way interaction and the possibility of applying without second lower terms with keeping the main variables in the equation not like the other questions. In fact the other ...
2
votes
0answers
40 views

Is two years enough for panel data analysis?

I have around 800 companies for only two years period. However, around 200 of them have only one year observation. Is it still possible to conduct panel data analysis with such data Thank you
1
vote
1answer
22 views

Is it possible to measure the independent variable with part of the dependent variable

I have Beta as my independent variable and Economic value added (EVA) as my dependent variable. To calculate EVA I need to use Cost of capital and to calculate that I have to use Beta, so is it ...
0
votes
0answers
35 views

How to interpret residual plots from time series regression

I am doing a time series regression between 2 variables. I used the dynlm library in R. I'm trying to understand how to interpret the results. Could you please point out where I am getting it wrong: ...
0
votes
1answer
33 views

Hodrick-Prescott derivation in lay terms

I am currently working with the Hodrick-Prescott filter. I would like to understand the equation in lay terms.
0
votes
0answers
20 views

How to down weight correlations in my microarray analysis?

Background: I have been tasked in one part of my analysis to reproduce a method used in another study as follows in bullet points form: Microarray data from a number of time points Calculate ...
0
votes
0answers
17 views

Autoregressive model with input variables in proc arima procedure

I am currently working on the time series analysis for series Y but I have to use other two variable A and B as an input variable in SAS proc arima procedure. But I am unable to interpret the cross ...
0
votes
1answer
16 views

How to use a set attributes of an entity at different time snaps to make predictive analysis?

The problem is to come up with a classifier for any task based on a set of attributes of an entity having different values at different times. For instance think about football players and their match ...
0
votes
0answers
10 views

Count variable as control variable in regression in SPSS

I'm doing a research on development of audit fees in 2005-2012. I'd like to see if there's a downward or upward trend in them. I have made a count variable of the years (2005=1 2012=8) and now should ...
0
votes
0answers
8 views

proportions at two times with predictor

I wonder if anyone can help me. My data has 3 main variables: proportions at 2 time periods, and an additional predictor. For example: Item Type Y(t) X Y(t+1) 1 .05 ...
3
votes
2answers
68 views

Learning to map vectors to vectors

Say we want to learn a function: $f(\mathbf{x} \in \mathbf{R}^p) \rightarrow \mathbf{y} \in \mathbf{R}^q$ where $\mathbf{x}$ and $\mathbf{y}$ are vectors representing time series. We have multiple ...
2
votes
1answer
25 views

How to isolate impact of event in a product's lifecycle?

I'm trying to figure out how a single event affects sales numbers of a song. For example, see what the effect of being featured in iTunes store compared to songs with comparable previous download ...
1
vote
0answers
23 views

Applying ARMAX model from r output

I'm trying to apply R output to generate a scenario using external data, I'm not sure how exactly to use the coefficients in each from the R output. I have an ARMAX(1, 1) model Coefficient of AR1: ...
2
votes
0answers
27 views

What kind of analysis gives you the statement "If you DONT reach X amount by time T, then your chances go down by P percentage?

I am trying to model growth for data I have regarding downloads of applications. I would like to make a statement, if you "DONT reach X amount of downloads by time T, then your chances of reaching 15 ...
0
votes
0answers
10 views

Signal dimension in regression model

Estimating Unknown Sparsity in Compressed Sensing is a paper about sparse signal. I am just learning the concepts. In the first paragraph, it says that when the number of observation data samples $n$ ...
0
votes
0answers
18 views

What is the procedure to compare two different period time series

I am currently working on the task that I would like to compare two different period time series like Sales in 2012 vs Sales in 2013. Kindly suggest me any statistical procedure.
1
vote
0answers
15 views

What is sparse regression model

I am learning the concepts of Sparse regression and facing initial hurdles in terminology. sparse regression model explains the definition of what is meant by sparse. When the number of samples $n$ ...
4
votes
1answer
61 views

Sample Mean of AR(1) model

Consider the AR(1) model with iid innovations with finite mean and variance. Also, let $X_0 = 0$. \begin{align} X_t = \phi X_{t-1} + \epsilon_t \end{align} The goal is to derive the asymptotic ...
2
votes
1answer
44 views

Model for probability of song reaching top 10 ranking, over time?

I'm trying to model the probability of a song reaching Billboards top 10 over time. My data has the columns "Day since release", "If reached top 10". For example, [12,1] means the song hit top 10 on ...
0
votes
0answers
13 views

How can I a “multiplier effect” in time series data?

I currently have data corresponding to how often a certain set of songs were downloaded. Each song has a release date, and then the number of downloads per day going forward to today. It would look ...
3
votes
0answers
191 views

Intervention With Differencing

When conducting an intervention analysis with time series data (aka Interrupted Time series) as discussed here for example one requirement I have is to estimate the total gain (or loss) due to the ...
2
votes
1answer
31 views

What is the best test to estimate the correlation between binomial/categorical dataset?

I'm trying to analyze if there are correlations between binomial dataset. I have binomial data (presence/absence) of two variables in different periods and I need to know what is the best way to find ...
0
votes
0answers
30 views

How do I estimate a time series regression using GMM in the way proposed by Acosta-Ormaechea and Morozumi (2013)?

In their paper Acosta-Ormaechea and Morozumi (2013) propose a use of GMM for estimating a regression in which they try to find the impact of reallocating public expenditure from some unproductive to ...
1
vote
1answer
59 views

Estimation of regression with autocorrelated errors

In a book it is written that, In regression work we typically assume that the observational errors are pairwise uncorrelated. But in most time series data , the successive residuals have tendency to ...
2
votes
2answers
118 views

Capturing Seasonality in Multiple Regression for daily data

I have a daily sales data for a product which is highly seasonal. I want to capture the seasonality in the regression model. How I can do it? I have read that if you have quarterly or monthly data, in ...
2
votes
2answers
136 views

R: Fitting a model with periodic, nonlinear and categorical components

Can anyone give me some advice on how to fit a model with linear (some categorical), non-linear and time series components in R? I don't want to use a non-parametric model like a Loess smooth or ...
2
votes
1answer
25 views

Can I difference after fitting a time series regression model?

Suppose that I have a time series that exhibits a notable trend, and I want to test a hypothesis that a second variable is related to that trend. I fit a linear regression model with that second ...
1
vote
1answer
29 views

ARIMA modeling with more than one Categorical Variable

I am using auto.arima for forecasting. I have more than one categorical variables having more than one level. My questions are : Do I need to do dummy coding ? ...
1
vote
0answers
76 views

F-statistic value is too high for my model

Number of obs = 501 , Method: Fixed-effects regression Number of groups = 101 F( 10, 100) = 3422.31 , Prob > F = 0.0000 , ...
0
votes
1answer
68 views

How to forecast time-series bounded by [0,1], i.e., forecast relative frequencies?

I am working with time series values which are all in the closed interval [0, 1]; these values represent relative frequencies, i.e., empirical probabilities. I would like to create a model such that ...
2
votes
0answers
41 views

Turning general regression into time-series prediction

Suppose you have a general regression model, which behaves like a black-box to you. All you have is a $\ \ \text{train}(X,Y) \ \ $ function, where you input your predictor matrix $X \in \mathbb ...
1
vote
0answers
16 views

How to fit two or more datasets with different occurence for regression

I want to run a regression in R with different datasets. The question is whether stock performance (daily log return) is influenced by factors like interest rates (the one set by fed or ECB), size of ...
0
votes
0answers
19 views

Regression line fit for linearly increasing data with manual reset

I've a linearly increasing time series dataset of a sensor with value ranges between 50 to 150 on which I've implemented a simple linear regression algorithm to fit a regression line, and I'm ...
1
vote
2answers
270 views

Estimate ARMA coefficients through ACF and PACF inspection

I know that this is probably a question that's been asked plenty of times, but i haven't seen an answer that's both accurate and simple. How do you estimate the appropriate forecast model for a time ...
1
vote
2answers
24 views

Can time be squared to develop a curvilinear model of crop yield against time?

I am developing a linear model of yield against time (33 years of yield data) where year is 1975,1976....2007. I want to know whether change in yield over time was linear or not. So I fitted a linear ...
1
vote
1answer
44 views

How can I detect spurious regressions results?

I run bivariate Granger-causality regressions. Let $y_{t}$ and $x_{t}$ be stationary time series. I test if $x_{t}$ can forecast $y_{t}$ with the following regression: $$y_{t+1} = \alpha + ...
2
votes
1answer
120 views

Can First Differencing Cause Negative Serial Correlation

Ex. series, say stock prices 103 101 102 150 101 102 100 First differenced 2 1 48 -49 1 -2 Notice you could guess a very large negative number following the very large positive in the first ...
0
votes
0answers
52 views

Mixing two linear regression models

In time series analysis, I have one predictor $X_1$ that has a higher $R^2$ when regressed against $Y$ sampled at 10 minutes interval. Another predictor $X_2$ has a lower error when fitted against $Y$ ...
1
vote
0answers
33 views

Estimating a first order plus dead time model

The data generating process is given by the following differential equation: $y(t) = a + b u(t - \theta) + c \frac {dy} {dt}$ Now imagine having as data a long time series for both $y$ and $u$. If ...
2
votes
1answer
76 views

Why could mean centering change results

I used centering for my variables due to multicolleanirity and surprisingly the results (from before to after centering) changed for two interacted variables; one from significantly negative to ...
0
votes
0answers
27 views

Centering vs. Standarizing which one is better? [duplicate]

Two approaches have been proposed in order to overcome the issue of multicollinearity if we have interaction variables which are mean centering and standardizing (z scores). You can check No.2 in this ...