Time series are data observed over time (either in continuous time or at discrete time periods).

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Do Difference-In-Differences Estimators Inherently Remove Seasonality?

I have crime data which are known to be seasonal, and I want to determine the effect of a treatment on the crime. I have a treated group and a control group which share similar characteristics. The ...
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7 views

Ideal statistical or machine learning technique to predict streamflow from snow albedo (highly cross-correlated)?

I'm trying to build a model that can predict streamflow for an alpine (snowmelt-fed) watershed using snow albedo (roughly, the energy reflectance of the snow) data. Albedo controls the melt of the ...
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9 views

volume and stock price [on hold]

I am trying to look at the relationship between option volume and stock price. For this I intend to divide my data into intervals of 5 mins (Link). Though I suspect there will be intervals for which ...
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1answer
13 views

Modelling a nonstationary variable with stationay and nonstatianry variables

I am very confused with a time series analysis. Ley "y" is the dependet variable which has an increasing trend. Let x1 is a price index for a group of goods. I know that x1 creates the general trend ...
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8 views

Need help setting up a model and running a test for significance

new poster here. I've taken very basic stats classes so I would like some help setting up a model testing the significance of an Act that was passed by the US gov't recently utilizing real data. ...
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13 views

Exponential smoothing state space model - stationary required?

I came across with the Exponential smoothing state space model for time series forecasting. My question is if it does require that the time series is stationary? Is there any paper that explicitly ...
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10 views

R packages for Durbin-Levinson algorithm and innovation algorithm for time series forecasting [migrated]

I am looking for a package in R that implements the Durbin-Levinson algorithm for time series forecasting in $AR(p)$ model and innovation algorithm for $MA(q)$ and $ARMA(p,q)$ model. I looked at ...
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31 views

Is this the wrong way to do cross-validation?

I am building an ARIMA model and did a grid search to find which values to use for my AR and MA components using the AIC criteria (this was using all of my data). The results are in this graphic: ...
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How can I compute cross-correlation and auto-correlation in R using pooled data?

I'm trying to perform a lagged linear regression on time series data sourced from ~10,000 hospital patients, for the purpose of estimating causal relationships between administration of a drug and a ...
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1answer
18 views

How to check if the data is intermittent or too many zeros are due to seasonality?

I have a dataset for weekly number of calls to a call center for three years.The data is seasonal (I know this from practitioners knowledge) which means that calls normally come on summer and winter. ...
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10 views

Finding correlation of periodic data

I am working on a hedging model for commodity.I have past 36 months data of commodity market price and future contracts price. e.g. on 1st April,2014, market price is x,April contract price = x+1,May ...
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Growth mixture modeling with latent variables in R with lcmm

I am trying to replicate the analysis that was used to make this figure: I have measured the depression levels (a quantitative variable) in my subjects at the following time points (in months): ...
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15 views

Survival analysis with time dependent covariates and cured fraction

I have a problem specified in this way, I'll make a fictional example, because the actual data requires quite a bit of domain knowledge to be understood. There is a series of newborn babies (let's ...
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53 views

Why do you have to use MLE instead of OLS in time series data?

I know it has something to do with the errors being correlated with the variable, but I'm not sure exactly what that means. Could someone please give me a quick simple explanation about why you must ...
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51 views

Interpreting regression results

I computed the following regression using R. ...
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8 views

How to test the significance of the Hurst parameter?

I am trying to fit a FARIMA model and I am using rsFit function in R to estimate the Hurst parameter (H). This function provides ...
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21 views

Vector autoregressive model selection process and relationship with cointegration

Let's say you're looking at two securities that trade closely with one another and you suspect you can somehow trade the spread. How can you use VAR models to estimate the relationship between the ...
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1answer
127 views

R Time Series Analysis forecast result always remains same

I am trying to do time series analysis in R. I have data time series data set like this. ...
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1answer
9 views

Using Diebold-Mariano test to compare predictive errors in non-time-series?

I understand that the DM test is established for time series data, but could I still apply the test for non-time-series data? Could I simply replace the autocorvaiance part of the test statistics with ...
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21 views

Appropriate Test for Statistical Significant Change in Values Over Time [duplicate]

I have four number of values for number of policies within a given field put forward in a given year. I want to find if there is a statistically significant increase or decline in the number of ...
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16 views

How to determine significant difference between two sets of time series data?

I have 2 sets of time series data. The data were collected from individuals who were matched (via propensity score matching) prior to collection. The only difference is that one set of matched ...
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22 views

orthogonalized impulse response's contradictory forms in a VAR(p) model

I have so far discovered three different ways of utilizing the Cholesky decomposition for calculating the OIRFs of a VAR(k). The different methods seem contradictory so I would like some input on ...
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16 views

How to find if there is a trend in a time series and stationarity

I would like to conclude on a given time series that if it has Trend or not. I have carried out a cox-stuart test in R and have decomposed to inspect the series visually but still a bit confused on if ...
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Why is stl function giving significant seasonal variation with random data

I plotted with following code with stl (Seasonal Decomposition of Time Series by Loess) function: plot(stl(ts(rnorm(144), frequency=12), s.window="periodic")) ...
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Forecasting and decomposition of hourly time series with 2 seasonal periods

I have hourly temperature data over a 5 year period with a lot of missing values. They have 2 seasonal periods: daily (24) and annual (365*24). I am very interested in the diurnal cycles of the ...
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1answer
46 views

Correlation between spot and futures

I am Airliner.I want to protect my business from price volatility of jet fuel cost.Jet fuel is not traded in futures market but Crude oil is traded in futures market. I have daily spot prices of jet ...
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40 views

Introductory data trend analysis with R [on hold]

I am new to the data analysis world and am struggling to find relevant articles / examples related to what I'm trying to do. I have a data set that is like this, for example how many apples are sold ...
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Frequency analysis from time dependent data in R

I've got a time dependent data from animal recording. My data has two groups (TR and UT) each group has 20 replicate. Tiempo (time) variable goes from 282 sec to 318 sec. I have a turning point at 300 ...
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115 views

How to interpret these acf and pacf plots

Following are acf and pacf plots of a monthly data series. The second plot is acf with ci.type='ma': The persistence of high values in acf plot probably represent a long term positive trend. The ...
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Identify distribution change [on hold]

I have a categorical variable Product that can have one of $4$ possible values, ${x_1,x_2,x_3,x_4}$ The current distribution is ...
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1answer
23 views

How can I estimate the delay between two non-periodic time series?

I'm wondering what the best way to estimate the delay and confidence between two non-periodic time series would be. Specifically, I thought it would be interesting to look at the different economic ...
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21 views

Forecasting one dataset using data and correlation from another using R: commercial centers entrances and restaurant sales figures

Please, be kind, as I'm totally noob in stats and R... I'm the owner of a small restaurant in a commercial center, and I managedd to collect two main dataset, commercial-center (cc) and restaurant ...
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1answer
29 views

Autocorrelation or Serial Correlation

Autocorrelation is also known as serial correlation . Why is the terminology serial used ? Is there anything unserial or ...
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22 views

Statistical evaluation of two time series

I have two time series. I want to know, how strong they differ from each other. Very important point is to show that for example all (or probably only the majority of the) points in the first serie ...
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1answer
29 views

Predict time series data from another

Here is my problem: I have two times series which are highly correlated. One of my time series have one more data point. I would like to predict the other time series missing data. For example (in ...
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41 views

Correlation Coefficient for lag $k$ in Time Series Data

Formula of Pearson Correlation Coefficient is : $$r_{xy}=\frac{\sum_{i=1}^{n}(x_i-\bar x)(y_i-\bar y)}{\sqrt{\sum_{i=1}^{n}(x_i-\bar x)^2}\sqrt{\sum_{i=1}^{n}(y_i-\bar y)^2}}$$ In Time series ...
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1answer
35 views

Is Predicted R-squared a Valid Method for Rejecting Additional Explanatory Variables in a Model?

I'm building a model to understand the important drivers from a set of possible drivers for a time series of data. In my case the possible drivers are other time series. Like most statistical models ...
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23 views

Time - series analysis data set should be converted to return or taken its Ln?

I'm studying time series in E-views. And I want to investigate Granger - causality between exports imports and economic growth. So, I'm doing causality and co-integration analysis. I have export, ...
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What measures can be applied to the arrival of unique website visitors to asses whether there is an increasing or decreasing trend?

I am looking at the logs of arrivals of unique visitors to a website. I can plot the data as a histogram, and look at the plot to get an idea of whether there is an increasing or decreasing trend in ...
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ARX model selection

I have an autoregressive model with exogenous variables: $S_{t} = \sum_{i=1}^{p} a_i S_{t-i} + \sum_q \sum_{i=1}^{r} b^q_i X^{q}_{t-i}$ where $S_t$ is the signal I want to predict and $X^q_t$ the ...
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116 views

Has anybody ever found data where ARCH and GARCH models work?

I'm an analyst in financial and insurance fields and whenever I try to fit volatility models I obtain awful results: residuals are often non-stationary (in the unit root sense) and heteroskedastic (so ...
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15 views

Aggregating Multiple Sparse Time Series

My data contains multiple time series, each representing a person's activity over time, grouped by month. The activity is defined by a single count variable indicating the magnitude of their activity. ...
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21 views

Ljung-Box statistic / AR-GARCH weak predictions

How would you interpret the Ljung-Box statistics in the following AR-GARCH output? What is the difference between the $R^2$ and $R$ Ljung-Box statistics? Does the GARCH model seem to be effective, ...
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21 views

Weekly frequency [closed]

I'm analysing weekly time series data. Years have different numbers of weeks, some 52 and some 53, but by time series assumption it has to be constant frequency. How can I fix frequency problem?
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How to know regression equations at optimal combination method for hierarchical time series forecasts? [closed]

I'm doing a comparison about forecasting hierarchical time series methods and I would like to know better how does optimal combination works (method proposed by Atanasopoulos, Hyndman and Ahmed). I ...
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1answer
20 views

Multiple Independent Variables, Multiple Dependent Variables and Time Series Data

I am conducting a research on stock market. My Independent variables are Oil prices, Exchange rate, Interest rate, GDP & Inflation. And Dependent variables are Market return, and Sector wise ...
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1answer
39 views

Testing two raters' time-point data for interrater reliability

My data consists of two raters interpreting one specific phenomenon to occur at different points in time (the observations are not paired, the raters actually identified different amounts of ...
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Sample time series to equal interval

I have data with timestamp and associated values. time interval between two consecutive data is not constant. How to standardize the the time series and associated value ? eg- Input data is Timestamp ...
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Considerations for forecasting

I am trying to make a generic forecaster for many short (~14 points) to long term (~365 points) time series data assuming the seasonal period to be weekly. The predictions are going to be made for a ...