1
vote
1answer
18 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
21 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
0answers
28 views

What types of statistical analysis technique available to compare two different time series [on hold]

I am currently looking for suggestion to compare or study the two different period time series like sales in 2000 and 2001. As it is sales of the same product and i would like to compare those two ...
0
votes
1answer
23 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
12 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
10 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
14 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
35 views

How to perform multilevel interaction [on hold]

Which model is correct and can be applied? $$Y=x_{1} + x_{2} + \left(x_{1}x_{2}2013\right)+ \varepsilon$$ $$Y=x_{1} + x_{2} + \left(x_{1}2013\right) + \left(x_{1}x_{2}2013\right)+ \varepsilon$$ ...
0
votes
0answers
9 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
62 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
23 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
21 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
39 views

Large regression models and multivariate model

Large Regression models says that a regression model is large if the signal dimension $p$ is greater than number of observations $n$. In AR(2) model $y_t = a1y_{t-1} + a2y_{t-2}$ the parameter is a ...
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
14 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
13 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
58 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
40 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
11 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
185 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
30 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
28 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
54 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
89 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
129 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
23 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
25 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
70 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
56 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
39 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
15 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
18 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
231 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
23 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
40 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
109 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
49 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
67 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
26 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 ...
1
vote
1answer
45 views

How accurate is F test in panel data

I heard that the F-test is to advice you whether to use fixed effects or pooled OLS. However, I didn't find any details about it in books. Only in a very few studies. What is the hypothesis of the ...
1
vote
0answers
53 views

Is it ok to transform a logarithm variable to z score

I have a variable that has 57 kurtosis, so I decided to transform it to log. However, I have multicolleanirity problem due to interacting this variable and others with another variable so I am using z ...
1
vote
1answer
26 views

Characterizing trend of time series in R

I have a fairly basic statistics application question. Lets say I have a set of four fold-change values, representing the abundance of a factor as it passes through four consecutive time points: ...
0
votes
0answers
11 views

Repeated measures with multiple time points for the predictor and dependent variable: Does Xt-1 predict Yt better than Yt-1 predict Xt?

I have a question on what type of analysis I should be looking into to analyze some data I have: Suppose you have 2 runners X and Y, and they take turns sprinting 100 meters, with runner X going ...
1
vote
1answer
68 views

structural breaks in time series using matlab

in a plot of my time series there is clearly visible that there is structural break, but I have to find the exact date. I want test this with the chow test. Although I understand how to perform this ...
1
vote
0answers
45 views

Time series, x-y coordinates, regression, R [closed]

I have data in the form of these columns: date, x coordinate, y coordinate, value A, value B, value C, value D, etc. (I don't see the possibility to copy an ...
0
votes
1answer
65 views

Multicollinearity with Interaction (high VIF)

When I check the VIF of my independent variables with the dependent variable, it looks normal and less than 5 but when I add the interaction variables, the VIF increase to 48 for some variables. I ...
2
votes
2answers
62 views

Prove expression for variance AR(1)

For the AR(1) process $x_t = \delta + \phi x_{t-1} + \eta_t$, I am trying to prove that the variance is: $\sigma_x^2 = \sigma_\eta^2/(1-\phi^2)$ And that the first-order covariance is: ...