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6
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0answers
31 views

Multivariant time series in R. How to find lagged correlation and build model for forecasting

I'm new in the page and pretty new in statistics and R. I'm working on a project for college with the objective of finding the correlation between rain and water flow level in rivers. Once the ...
-1
votes
0answers
8 views

Lag Selection in ARDL model

I would like to apply ARDL model to compute the impact of changes one price on inflation. But I don't know how to compute the lag value of dependent and independent variables. Please help.
1
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1answer
37 views

Correlating two time series to account for lag and lingering effects

I am trying to find the correlation between two time series, call them A and B. Let's pretend A has the number of successful advertising campaigns for each month for a company, and B has the company's ...
0
votes
0answers
26 views

ARDL, Lag Terms and Singularity

I am interested in fitting an ARDL model that has 4 lags for each explanatory variable. However, when I fitting the model in R. R says that coefficients are not defined because of singularities. Is ...
1
vote
1answer
74 views

Autocorrelation for regression

I am attempting to use a significant autocorrelation (where it lies outside a 95% interval around 0) indicating periodicity of a signal and use it as predictive variable in a regression. If, for ...
1
vote
1answer
128 views

How is the proper number of lags for ACF or PACF displaying?

How many lags should be used for ACF or PACF displaying if we have $S$ seasonality? For example, for 500 observations I have 25 lags for 200 observations I have 22 lags It is independent from ...
0
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0answers
42 views

Using kknn regression function with NAs

I have been lurking here for awhile and now have a question I hope to get answered! I am wondering how to get nearest neighbor algorithms to deal with NAs most effectively. I am dealing with a data ...
1
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0answers
73 views

How to interpret results after including lags in panel data regression (fixed effects)?

I would like to ask a question about lags I've included however I believe it's better if I first give you some more insight information about my topic. My hypothesis is ''the positive sentiment ...
0
votes
0answers
50 views

Sum of lagged coefficients (VAR)

I have come upon a paper where a VAR analysis is performed. Using 3 endogenous variables and some exogenous (control) variables, the results of the VAR analysis are shown in a table. For the ...
0
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0answers
30 views

What is the problem with my lagged variables?

There are variables a,b,c, and d. Variables a and b is from firm's financial statements and they have time-lag.(financial statements take time to be announced) Variable d is a dummy variable ...
2
votes
1answer
393 views

Intuition behind cross-correlation function interpretation vs. correlation of lagged time series

Can someone please explain the difference behind WHY the cross correlation function ccf() chooses to keep the same denominator for all lags and chooses to ignore ...
0
votes
1answer
159 views

Interpreting Linear Model Coefficients with Lagged Variables

Let's say I have a data set which looks like below and I'm running a linear model to predict income on two predictors. ...
9
votes
1answer
368 views

When is it necessary to include the lag of the dependent variable in a regression model and which lag?

The data we want to use as dependent variable looks like this (it is count data). We fear that since it has a cyclic component and trend structure the regression turns out to be biased somehow. We ...
1
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0answers
91 views

Shrinkage Estimator for Newey-West Covariance Matrix

This is a cross post. I would like to apply the Newey-West covariance estimator for portfolio optmization. Up to lag one it is given by $$ \Sigma = \Sigma(0) + \frac12 \left (\Sigma(1) + \Sigma(1)^T ...
1
vote
0answers
102 views

Lagged term in time series with stationary errors: too good to be true?

I often have datasets where there are many animals, in several treatment groups, and each animal's body weight is measured at regular intervals over the course of its lifetime. The response of body ...
0
votes
0answers
115 views

Lagged dependent variables and dummy interaction terms interpretation

Quick question about interpreting lagged variables. It is my understanding that if I have a regression with 2 lagged dependent variables, the marginal effect of the lagged dependent variable is the ...
2
votes
1answer
183 views

How to fit a model with lagged variables

I am trying to fit a model with lagged variables. The problem is: In a big classroom with windows open, the outside temperature, humidity and solar activity will lead to variation in the ...
5
votes
0answers
59 views

Inducing autocorrelation by fitting the wrong ARMA?

I am trying to fit an ARMA(p,q) model to the mean equation of my return series. The problem is, that the acf and pacf are pretty not usable, i.e. it is hard to find a good model to take account of the ...
0
votes
0answers
45 views

How should I interpret the (Bartlett) lag window in this equation?

I'm trying to apply a technique for identification of structural breaks in a financial time-series (so heteroskedastic) and one of the estimators is defined as follows: $$ \hat{\omega}_4 = ...
0
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0answers
184 views

STATA - Procedure for properly estimating an AR(p)

I'm trying to estimate an autoregressive process AR(p). Following the literature: 1) I checked if the series is stationary or not running the augmented Dickey-Fuller test (as I expected, the ...
0
votes
1answer
78 views

Running a Probit on Survival-Time Data?

Can I run a probit on survival time data? It's discrete-round, and I want to look at whether lagged variables affect the failure event. I am, however, getting negative coefficients for a probit ...
0
votes
0answers
45 views

Polynomial distributed lag glms

I am about to use this input for my data but i cant find under which packages does it work. I searched almost everywhere. m<-pdlglm(yy~pdl(zz,4,2)+sin(zz)+pdl(xx,4,4))
0
votes
0answers
368 views

How to use Almon model (polynomial distributed lag) in R program

I am testing the influence of intramural R&D expenditure, life expectancy, HDP and tax on the GINI index, but I have a problem because I am trying to make my model better by using the Almon model ...
6
votes
2answers
3k views

Inclusion of lagged dependent variable in regression

I'm very confused about if it's legitimate to include a lagged dependent variable into a regression model. Basically I think if this model focuses on the relationship between the change in Y and other ...
1
vote
1answer
192 views

Issues when using interaction term with a lagged variable in R

Today I tried to estimate models using both plm and pgmm functions in the plm R package, with an interaction between ...
3
votes
0answers
462 views

Lag length selection Granger causality test

Consider G-Causality on two stationary time series vectors (call these variables $X$ and $Y$), each with 100+ observations. It's daily financial market time series data. I have reason to believe that ...
1
vote
1answer
288 views

Vector autoregression - number of lags

I am constructing a Vector autoregression model and I have used AIC to find how many lags I should use. Does 7 lags seem unreasonable? I am trying to find the impact the property market has had on the ...
4
votes
3answers
2k views

Creating auto-correlated random values in R

We are trying to create auto-correlated random values which will be used as timeseries. We have no existing data we refer to and just want to create the vector from scratch. On the one hand we need ...
3
votes
2answers
2k views

Correlating volume timeseries

Consider the following graph: The red line (left axis) describes the trading volume of a certain stock. The blue line (right axis) describes the twitter message volume for that stock. For instance, ...
1
vote
2answers
822 views

Lagging over a grouped time series

I have a few tens of thousands of observations that are in a time series but grouped by locations. For example: ...
3
votes
0answers
235 views

Lag Selection Modelling 'Pseudo' Panel Data

I have what I would call a pseudo panel, where my dependent variable varies over time and space (regional death counts), but my x variable of interest does not (national wage time series). Basically, ...
3
votes
2answers
516 views

How to account for lag in a simple regression in R?

I'm trying to do a regression with data over time, and where I suspect there may be a lag component in the relationship between my dependent and independent variables. I've actually found some data ...
2
votes
0answers
200 views

Using autocorrelation plots to choose the number of inputs for a neural network predicting time series

A neural network applied to time series needs to have the number of input nodes defined. Each input is applied to a time point previous to the current point being predicted. If $D$ is the number of ...
1
vote
2answers
547 views

What is wrong with lagged regressor in time series regression?

I am trying to explain a time series with the help of other related series. I really get nice fits using a standard LM approach with NeweyWest VC matrix. The fit even increases drastically when I ...