0
votes
0answers
27 views

R function which uses innovations algorithm?

I can't seem to find much info on the following: I have a dataset D at time t which I use to fit an ARIMA model. I forecast the value of the time series at time t + 1. Now, when I'm in t + 1, I would ...
0
votes
0answers
13 views

Determine the threshold value and number of regimes with delayed variable

I am currently working on a threshold model for the exchange rate between UK and US. I have not got background knowledge on this model so I am really stuck on how to determine the Threshold value, ...
0
votes
0answers
32 views

Problem when doing pre-whitening before ccf analysis [migrated]

I have following R code which does not work when trying to pre-whiten other series by the model generated for the other series. ...
1
vote
0answers
27 views

Where can I find resources to learn about change-point analysis ?

Where can I find resources to learn about change-point analysis ? Hopefully, someone can advise me a textbook to read and it will cover both univariate change-point analysis and multivariate ...
0
votes
0answers
29 views

Arima model - multi step forecast

The following code shows a forecast of the next 24 hours of my electricity prices with two exogenous variables. My problem is, that I don't know how to build a forecast for the next 3 days or more ...
-1
votes
0answers
25 views

Is this the proper way to create a simple linear time series model in R

I'm trying to create a simple ols model over time from a time series. Here's what I have cagr.lm.time <- lm(cagr.xts ~ time(cagr.xts)) Where cagr.xts is the ...
0
votes
1answer
71 views
+50

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 ...
0
votes
1answer
28 views

MAPE is high for daily sale prediction

I have daily sales data from 2011 to 2013. I have to do prediction for 2014.I have used arima and exponential method to predict the daily sale, but it is not giving the better result. MAPE is around ...
0
votes
1answer
17 views

Getting expected value of future value with time varying data (credit card revolving and fee data) . Customer lifetime value

I have a credit card data and that contains monthly amount of revolving and amount of fee for each customer. As a bank perspective, I want to get the expected value of future revolving amount and fee ...
0
votes
0answers
43 views

Calculate the average of hourly data of three sensors

I am trying to calculate the average of hourly data of three sensors but the hourly timestamps of all three sensors are different. How is it possible to measure the average of hourly data of all three ...
1
vote
3answers
128 views
+50

How to perform proper data mining on time-series data?

I have some daily data from city A, B, C. Values from city A are highly correlated with values from other cities for lag -1,-2,-3 and -4. I want to use Random Forest, SVM and ANN to predict values ...
0
votes
0answers
30 views

Forecasting agricultural commodity prices with R

I would like to create a predictive model in order to forecast the price of an agricultural raw material. I got time series for the prices and the production of this raw material, and also for the ...
1
vote
0answers
13 views

Testing for heteroskedasticity of time series in R

I wish to test my time series data for volatility clustering, i.e. conditional heteroskedasticity. So far, I have used the ACF test on the squared and absolute returns of my data, as well as the ...
1
vote
1answer
22 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
19 views

How to approach time series regression with one continuous variable and one “ almost Boolean” variable?

I am working in R with daily time series data and have daily observations of two variables. The first is continuous. The second is zero for every day except one, in which it is a number (I'm not sure ...
1
vote
1answer
16 views

Stationarity consideration in ARIMA using KPSS test

I have data, which I am sure has a downward trend. I am trying to forecast this data using ARIMA and I want ARIMA to consider the trend when it is forecasting. The first step in ARIMA is to ...
-1
votes
1answer
70 views

Time series with negative data in R [closed]

I have data for forecasting like, here negative value is actual data ...
1
vote
0answers
12 views

Tail index using hill estimator in R [migrated]

As part of my data analysis (of heavy-tailed data) I wish to calculate the tail (for both left and right) indices of around 100 time series of company returns. My data is stored in a large zoo object, ...
1
vote
3answers
63 views

Intervention Analysis Coding in R TSA Package

I am studying intervention analysis in time series with the Cryer and Chan book and am looking at trying to understand how to code the step response interventions. One question I had is how to ...
0
votes
0answers
16 views

Outlier treatment in Vector Autoregression (VAR) Model using vars package in r

I have the same problem as the following post, but I have more samples and the index of the outlier is known. Outlier treatment in Vector Autoregression (VAR) Model I tried deleting the outliers; ...
0
votes
1answer
52 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 ...
1
vote
1answer
30 views

Combinef in R HTS package- constrain to keep forecasts positive?

When using the combinef function from Rob Hyndman's very useful hts package for forecasting hierarchical and grouped time series, there does not seem to be a way to constrain the optimally combined ...
0
votes
0answers
16 views

Specifying a glmm for panel data

I'm trying to predict counts based on variables sampled on a monthly basis as well as a few that are not related to time. In several places I've read that the MCMCglmm package in R would be ...
0
votes
1answer
32 views

Multivariate Time Series

I am trying to learn multivariate time series using R. I have two time series and I want to see if I could use one of those to predict the other one, and after that check if the model holds or there ...
0
votes
0answers
8 views

custom axis labels plotting a forecast in R [migrated]

I'm trying to get some sensible labels on a forecast. Here's my code: ...
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 ...
1
vote
2answers
53 views

R: How to to simulate ARIMA using starting values?

I have built an ARIMA(p,d,q) model, m using say, m <- Arima(ts.data, c(p,d,q)) Given some starting values, I want to simulate future values based on the ...
1
vote
2answers
188 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 ...
0
votes
1answer
26 views

Measure accuracy of Holt-Winters model

I'm really confused about measuring the accuracy of Holt-Winters fitted models applying different transformations. How do i compare the accuracy between models when i apply no transformation to the ...
0
votes
1answer
65 views

Analysis of spatial data over time and space

I have a data set having year-wise monthly average of minimum and maximum temperatures of 32 stations around the country since 1948. The latitude and longitude of the stations are given as well. I ...
0
votes
0answers
12 views

Error running optim function with STAR from book example

I'm running an example of Smooth Transition AR (STAR) Model from the book "Analysis of financial time series, 3rd edition" by Tsay, in section 4.1.3. The script is as follows: ...
1
vote
0answers
40 views

Rolling Window Forecasts in R

I have a question: how do I use rolling window forecasts in R: I have 2 datasets: monthly data which I downloaded from Google. monthly data I downloaded from the CBS (central bureau of statistics ...
1
vote
1answer
42 views

Forecasting a time series with weights

I'd like to forecast (or predict) a time series with weights. The following works using the regular linear modelling techniques ...
1
vote
0answers
44 views

Consequences of modeling a non-stationary process using ARMA?

I understand we should use ARIMA for modelling a non-stationary time series. Also, everything I read says ARMA should only be used for stationary time series. What I'm trying to understand is, what ...
1
vote
0answers
35 views

How do I deal with asynchronous data in financial time series?

I have tick by tick data of two financial time series. I am trying to do online regression between the given two time series. But I am stuck due to asynchronic nature of given financial time series ...
0
votes
0answers
58 views

Forecasting in R using forecast package

I'm trying to forecast hourly data for 30 days for a process. I have used the following code: ...
1
vote
1answer
25 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: ...
1
vote
2answers
43 views

Imputing missing observation in multivariate time series

Suppose I have a dataframe consisting of six time series. In this dataframe, some observations are missing, meaning at some timepoints all time series contain a NA-value. In R, one possible imputation ...
0
votes
1answer
80 views

Machine-Learning algorithms for Forecasting

For work, I'm working on an app where you essentially forecast the failure rate of the overall machine through different factors such as the historical failure rates for the components used to build ...
1
vote
0answers
41 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
39 views

R GMM - Error in solve.default(x$v, gb) : system is computationally singular: reciprocal condition number

I'm having the following problem estimating something in GMM in R. I have created a "Hello World" below. In principle, I would not need GMM to estimate the parameters, but I want to use it to obtain ...
0
votes
0answers
36 views

understand forecasts in linear state space models

The Kalman Filter provides the one-step-ahead forecasts within the recursions. We start estimating the (unkown) variance of the parameters for instance through MCMC ...
2
votes
1answer
53 views

what is K in fourier function of R

I am using fourier() function of R which has arguments x,h,K. Can any body please explain me what is 'K' in this function and what is the use of it. Thanks in ...
1
vote
1answer
27 views

Estimating auto-correlation with unequally spaced data

I'm working on a time series problem where the spacing between observations is usually 12 or 24 hours, but this is not guaranteed. I'd really like to estimate the auto-correlation function, and I've ...
0
votes
1answer
21 views

How to determine if two time series are significantly related to each other

Based on our knowledge of other characteristics of these two variables, we have reason to believe that changes in admits to a ward has an impact on a certain bad outcome on that ward (these are counts ...
2
votes
1answer
54 views

find the point at which the curve significantly shoots up

so this is getting a little complex for me and hope someone can help me out. I do not have a mathematical background. I have a time series of daily rainfall for 50 years for a particular location. ...
1
vote
1answer
32 views

Predicting time series with OpenBUGS

I have a number of fairly short time series (about 4–100 observations) which I need to forecast into the future. I decided to use Bayesian inference, because there is external information about each ...
0
votes
0answers
35 views

R intercept in arima with xreg

I am trying to understand what the reported intercept is showing when I use arima() with xreg=. The documentation says "If am ...
0
votes
1answer
27 views

Repeated measures design with measurements from different groups of animals

In a repeated measured design we measure a particular variable at different time points from the same subjects. In animal experiments, if animals are sacrificed at every time point to measure a ...
0
votes
0answers
47 views

Computing a distance matrix between multiple multivariate time series

This question has also been asked on stackoverflow.com. Yet my aim is to ask for efficiency gains on the aforementioned platform. My aim here is the correctness of my approach. I am trying to cluster ...