0
votes
0answers
6 views

Construct matrix of stacked variables in VAR regression

I am trying to NOT use packages for the estimation of models in order to have a deeper understanding of how things work. Currently, I am trying to estimate a VAR(1) (vector autoregression of first ...
1
vote
0answers
25 views

Regression - volatility vs return

I am attempting to estimate a linear model as: $$ y = a +bX +e $$ I have a series of annual returns and I would like to estimate the effect of volatility on losses. My Null hypothesis is that ...
2
votes
1answer
37 views

The effect of ommission of relevant variable in the regression model on adjusted $R^2$

Let's say I have two regression models (I) $y_t=\beta_1+\beta_2 x_2+u_t$ (II) $y_t=\beta_1+\beta_2 x_2+\beta_3 x_3 + u_t$ How the omission of relevant variable (not irrelevant variable) affects ...
0
votes
1answer
21 views

How to Build a Foresight System?

For a research project, I'm asked to find ways to build an economic foresight system. For example, for the production of cheese. We will have data about the market indicators, like price, demand etc. ...
0
votes
1answer
42 views

How to find which time series is trending more?

Let us say I have two sets of time varying series as shown below: ...
2
votes
0answers
40 views

Time series prediction where each datapoint has a sequence

I am Computer Science major, and new to stats, so please bear with me and point me to the right direction if what I'm asking is pretty obvious. I have a dataset, where each data point consists of ...
0
votes
0answers
22 views

Using day length and rate of change of day length in linear regression

I have a time series in which samples were collected approximately monthly over ten years. I have wanted to identify whether a number of bacterial species were seasonally variable and whether they ...
0
votes
0answers
25 views

Regression when you have both I(1) and I(2) processes

I want to estimate $\log Y_t=\beta_0+\beta_1\log X_{1t}+\beta_2\log X_{2t}+e_t$ Using ADF-tests, I have found that both $\{\log Y_t\}$ and $\{\log X_{1t}\}$ are I(1) (i.e. they contain a unit root), ...
0
votes
0answers
6 views

automation code for dynamice regression with arima in r [migrated]

I want to make automation code for dynamic regression with arima..where i just have to insert dataset and all calculation will be done automatically and store model,graphs,MAPE,etc below are the ...
1
vote
1answer
47 views

Separating Base and Promotional Volume

I am working on a project where I have to separate base and promotional volume from the sales data. I have sales data for the last 4 years at week level. How can I separate base and promotional volume ...
1
vote
0answers
14 views

Shrinkage estimation for regression with ARMA errors

I was wondering if someone knows a R-package or function library for the topic of shrinkage for regression with ARMA errors. Please let me know if you came across something related. Thank you! ...
1
vote
1answer
31 views

Difference between iid data and non-iid data for a simple regression problem

I am trying to understand the difference between iid and non-iid data. Let's consider a given time series, and say it's reasonable to assume that at each time point the random variable $X_t$ depends ...
0
votes
0answers
19 views

R: One period our cross validation with time series

I have quarterly data with one causal variable (X) and one dependent variable (Y). 30 such observations. I have the X variable for a quarter, and I'm seeking to predict that quarter's Y. The ...
0
votes
0answers
18 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 ...
0
votes
1answer
21 views

Regression with TBATS error?

I'm working on a time series model which includes multiple seasonal components (daily and weekly). I believe the best way to approach this would be BATS/TBATS model, however I have a concern if I can ...
2
votes
1answer
103 views

How do I interpret regression coefficients with autocorrelated residuals?

I am building a regression model of time series data in R, where my primary interest is the coefficients of the independent variables. The data exhibit strong seasonality with a trend. The model ...
0
votes
0answers
27 views

Financial Time series prediction/ SV Regression

I'm working with R software (Lib e1071) and I'm trying to get predictions using Support Vector Regression. The way I'm doing it is the following: I'm windowizing the raw closing prices using N=3 ...
0
votes
1answer
78 views

Fitting a time-varying coefficient DLM

I want to fit a DLM with time-varying coefficients, i.e. an extension to the usual linear regression, $y_t = \theta_1 + \theta_2x_2$. I have a predictor ($x_2$) and a response variable ($y_t$), ...
0
votes
0answers
32 views

Multiple time series methods for trend identification, forecasting etc

I have several time series consisting of aggregated macro-economic indices and I am trying to choose one or several appropriate techniques in order to answer a number of questions. First, I need to ...
0
votes
1answer
81 views

Can we apply multiple regression on time series data?

It always create a doubt to me, whether we can apply linear or non linear multiple regression on time series data. If yes, should I consider year also an independent variable. Thanks, Arushi
0
votes
1answer
58 views

Having difficulty forecasting a tslm model

I'm having issues forecasting a model of the following form. y1 <- tslm(data_ts~ season+t+I(t^2)+I(t^3)+0) It fits my data very well, but I run into a problem ...
0
votes
0answers
53 views

What statistics to use for testing hypothesis about regression coefficient when n is greater than 30

What statistics to use for testing hypothesis about regression coefficient when n is 120. I plan using a z score but am not sure.
3
votes
0answers
55 views

What are the stationarity requirements of using regression with ARIMA errors for inference?

What are the stationarity requirements of using regression with ARIMA errors (dynamic regression) for inference? Specifically, I have a non-stationary continuous outcome variable $y$, a ...
5
votes
2answers
153 views

Ordinal/continuous vs dummy variable for time series regression/data mining

Let's suppose I have a time series data that I would like to regress $y$ on $x$ and $Time$. See below for the dataset. ...
1
vote
2answers
70 views

Linear regression for time-series prediction

Say we have $N$ time series $X_t^i$ for $i=1...N$and we want to predict a separate time series $Y_t$. Let's consider the following model: $Y_t = \sum_{i} \beta_i X_{t-1}^i $ I am just trying to ...
1
vote
0answers
47 views

Problems and alternatives to using a four month lag in a linear regression model

Let's say I'm constructing a linear model with the intention of predicting automobile sales volume. Let's say that the consumer auto purchasing cycle takes 4 months, and so we'd 'lag' each observation ...
2
votes
0answers
46 views

Treatment of missing values introduced by padding lagged variables

In the case of a linear regression with lagged independent variables, what are the techniques for dealing with the NA values introduced by padding lagged variables (since t < 0 values do not ...
2
votes
1answer
88 views

Time-varying Coefficients

I have time series data on fish catches from 1950-2011. I wish to implement a regression model with varying coefficients. I'm aware that cox models etc. exist and implementation via the ...
0
votes
0answers
26 views

F-Test for comparing autocorrelations across groups

I've read a paper where they compute an $F$-test for the hypothesis that the autocorrelations of two groups are equal. Specifically, they estimate the autocorrelations of two time series $x_t$ and ...
0
votes
0answers
28 views

Time series feature selection: 20 independent variable, 1 dependent variable, 13 observations

I understand the challenges associated with the small # of observations. Nevertheless, some of the predictors have very powerful signals. The question is, how does one use R to most efficiently code ...
0
votes
1answer
252 views

Marketing Mix Modeling for sales data

I have data for 4 years with variables year, month and sales volume only. I want to find the base volume and incremental volume. I want to use Marketing Mix Modeling. Can anybody tell how to define ...
2
votes
0answers
47 views

Asymptotic distribution for t-test with time series

I once read the following statement: Given the following equation $ Y_t= c + a Y_{t-1} + \theta_t$ If $c\neq 0$, then the t-ratio for testing $H_0 : a=1$ is asymptotically normal. If $c=0$, then ...
0
votes
0answers
58 views

PACF and ACF for AR and MA

I once heard the following statement: ...
0
votes
0answers
34 views

Finding a leading indicator of a time series

I am interested in finding a leading indicator of $Y_t$. Is it sufficient to find a variable $X$ for which its lagged value is correlated with $Y$? Do I have to give consideration to the spurious ...
0
votes
0answers
33 views

Parameter Estimation

I have the data in the form of $Y \in \mathbb{R}^T$ a time series. For each point in time I have $ m $ real features $ f_i \in \mathbb{R}^m$. I want to use the following model to fit the data $ ...
1
vote
1answer
54 views

Multiple linear regression question

I am running a multiple regression of the form Y = $\beta_0$ + $\beta_1$*$X_1$ + $\beta_2$*$X^2_1$ + $\beta_3$*$X_2$ + $\beta_4$*$X_3$ on a time-series dataset. I want to plot the relationship ...
0
votes
0answers
30 views

Correct time lag in regression

Let's say you have two time series. you know they are highly correlated with the right time lag. Is there a function that's used to calculate the correct time lag, or do you just have to run a bunch ...
1
vote
1answer
77 views

What does it mean to 'align data frequencies'?

If I have two variables that have different sampling frequencies, one of the first steps is to align the frequencies; could someone explain the intuition of this alignment without being too technical. ...
1
vote
0answers
72 views

Problem of simultaneity

I have a question about solving simultaneity in this following case: Environmental taxes have direct and indirect effect on the change of waste pollution (ΔI). This effect (ΔI) has an indirect ...
2
votes
1answer
208 views

Shanken (1992) correction for t-statistics

I have done a cross-sectional regression of time-series average returns on estimated Betas (over the same time horizon) to determine average premiums. So far so good. But I was told that the standard ...
-1
votes
1answer
319 views

Linear/Non-linear Regression - SPSS

Hopefully somebody will be able to shed some light on my SPSS problems! I have been given 65 values. 57 of these data values are quarterly results and 8 are the holdback data to be used. I have to ...
0
votes
0answers
19 views

checking for autocorrelation with many observations and few time periods

How would I go about checking for autocorrelation if I had a few thousand observations for each time period and had about 15 different time periods? The data set I am working with has a lag variable ...
0
votes
1answer
76 views

Regression on time series and its segment series

I want to test whether segment series explains anything in additional to the full series. Let's say y and ts_full are time series with same length. And I divide ts_full to 3 non-overlapping sub time ...
2
votes
2answers
128 views

Best way to visualize predictions from a linear model

Let's say I'm doing some predictive analytics and am trying to predict US GDP per month using a two or three month lag. After every month, I generate new predictions and am able to compare my ...
0
votes
1answer
55 views

How can I find out how shifts in a country's fiscal policies affect its economic health?

I have the values of certain variables for 20 years for different countries... I am unable to understand how to use the values of a particular variable for 20 years. Could anyone suggest how I should ...
0
votes
2answers
116 views

Time series as cross-sectional data

I have time series, for example, gdp and unemployment(unemp), freq= 4. What if I interpret it as cross-sectional data and do cross-sectional analysis instead of ...
0
votes
0answers
62 views

Interpreting a regression modeled on twice differenced data

I have built a OLS model with data that was twice differenced. As I understand (and maybe I'm wrong) the coefficients (betas) can be applied to the original undifferenced data to provide Y at that ...
0
votes
0answers
51 views

Help with panel-data in excel

I want to know if the initiation of a state Renewable Portfolio Standard affects the level of renewable energy output in that state. I don't have access to Stata right now, so I'm stuck using excel. ...
6
votes
3answers
154 views

Does zero correlation between 2 differenced series implies no cointegration between original series?

The question is related to this one. In this question @mpiktas gives an answer on why checking correlation is not enough but the answer doesn't seem completely correct to me for the following reason: ...
1
vote
3answers
134 views

What model should one use for this short time series?

Below I have quarterly total sales on the left (dependent variable), and a sample of the sales on the right. The two variables share a correlation of 98.7%. What model should I use to predict X? ...