1
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1answer
28 views

Dealing with different time series data in Machine Learning

I am trying to create a stock market model based on fundamental variables for the US economy. I am using R. Some of the variables I am looking to include are: GDP, Unemployment Rate, Initial Claims, ...
0
votes
0answers
10 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 ...
0
votes
0answers
17 views

Calculate first difference by group in R [migrated]

I was wondering if someone could help me calculate the first difference of a score by group. I know it should be a simple process but for some reason I'm having trouble doing it..... yikes Here's an ...
2
votes
0answers
20 views

Statistical method to find capacity limits?

Im analyzing time-series to detect when the y-value is so flat that one can assume there is an underlying factor limiting y from being higher. Is there a methodology or statistical discipline that do ...
4
votes
2answers
182 views

Data mining techniques in R for advertising and sales data

I would like to apply one or more data mining techniques to a dataset, in order to see the effect advertising has on sales. I am working from this dataset. It has 36 consecutive entries of monthly ...
1
vote
2answers
63 views

Time series analysis: Determine if trend is deterministic fluctuating/stable or stochastic

I am analysing sales data of certain products and need to determine if the demand trend is deterministic fluctuating or deterministic stable or stochastic. How do I do that in R / what approach is ...
2
votes
0answers
24 views

Temporal Correlation in R

Having used stack overflow for years without signing up I now truly need some help! My data consists of samples collected from the same location in three different streams between 2012-2014. The data ...
3
votes
0answers
40 views

Entropy estimation for a symbol sequence

I am looking for an R-implementation of the Lempel-Ziv data compression algorithm, to estimate the source entropy of a time-series consisting of a sequence of symbols. Rather than simply measuring ...
1
vote
0answers
30 views

Neural net model - error during training

I'm getting started with R, I really like it but recently I found myself in a corner. I'd like to build neural network model that predicts heat consumption. I have historical data that contains ...
0
votes
0answers
43 views

What is the difference between forecasting based on ARIMA and logistic curve? R

I'm making a project connected with identifying the dynamics of sales. My database concerns 26 weeks (so equally in 26 time-series observations) after launching the product. This is what my database ...
1
vote
1answer
64 views

Forecasting with holiday dummy variables

I have an example of call center data for 2013. There are 261 days of data (excluding weekends). For 2013, I have included a holiday dummy variable (holiday) for ...
2
votes
1answer
39 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 ...
1
vote
2answers
66 views

Clear steps to calculate coherence between two time series

I originally posted this on stackoverflow.com and then deleted it and moved it here My question is similar to Similarity of two discrete fourier tranforms (specifically the selected answer). I've ...
2
votes
2answers
109 views

Special method for forecasting on time-series clusters in R?

I'm doing a project related to identifying sales dynamics. My database contains 26 weeks after launching the product (so 26 time-series observations equally spaced in time). I used two methods ...
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: ...
0
votes
1answer
22 views

Detection of periodic patterns using DWT

Is it possible to detect a periodic pattern in a time series using discrete Wavelet Transform? Is there any package in R to do this job?
0
votes
0answers
22 views

Statistical models that incorporate factors stepwise?

I am working on a dataset in R that essentially follows 20 groups of individual organisms through time. I am interested in assessing what factors impact their mortality. I have 5 factors that I have ...
0
votes
0answers
22 views

Plotting a timeseries in R as stacked bar [migrated]

I have a dataset that look like the following | SUBJECT | ACTION | DURATION | |---------|--------|----------| | 1 | A | 39,57 | | 1 | B | 1,48 | | 1 | B | ...
0
votes
0answers
14 views

High Ljung-Box p-values at large lags

I am trying fit an ARIMA model to stock returns. I have reached a decent model using the AIC criterion. However, the ljung-box p value under a diagnostic plots are pretty weird. The null ...
0
votes
1answer
57 views

time series is obviously periodic, but seasonal decomposition is not working in R

my time series is obviously periodic, but the seasonal decomposition using stl() is not working in R: ...
4
votes
1answer
81 views

Estimation/simulation of homing with time effect

I have birds translocated from site A (original, capture site) to site B (new, release site) and I want to analyse homing behaviour. Translocation of individuals was performed continuously (several ...
0
votes
0answers
24 views

Forecast mean and variance for group data

Apologies if this is a bit of a simple question, but I haven't been able to find any answer to this over the past week and it's driving me crazy. Background Info: I have a dataset that tracks the ...
0
votes
0answers
20 views

Choosing the best time series for forecasting

I have set of time series for various days (same frequency and source). I need to choose a subset of it, and they together will forecast future values. Currently I am simply using X out of Y time ...
0
votes
0answers
40 views

How to make Dummies with R [migrated]

I'm trying to forecast the daily electricity market price, with a dataset of 3 years before of daily prices, and we want to correct some seasonal effect because we cannot predict the prices, we want ...
4
votes
0answers
96 views

How to fit log-linear poisson autoregressive mixed model?

I have time-series count data $N_{i,j}$ (population sizes in site $i$ and year $j$) and I want to correlate year-to-year changes with the environmental conditions $x_{i,j}$. For this, I want to fit ...
0
votes
0answers
4 views

Find overlapping time periods among multiple irregular time series in R? [migrated]

I have multiple irregular time series. Each time series is from one replicate. After removing bad data (instrument failure) there are many gaps in all replicates. I have created a data frame ...
0
votes
0answers
12 views

How to get forecast using `stlf()` in R [migrated]

I am new to R. I am using the stlf() function in the forecast package to forecast trends in air passengers using the following code: ...
0
votes
0answers
15 views

Which method(s) for forecasting time series of event durations

I have the $N$ individuals each observed for $T$ days. For each individual I have some basic demographic data. Each $n$ individual, during the observed time $T_n$ may experience event $E$ which is ...
0
votes
0answers
44 views

Time series and stationnarity tests

I perform some time series fitting with the help of the forecast and urca packages. I have a question regarding the correspondance between results coming from statistical test such as KPSS, ADF or ...
2
votes
0answers
20 views

Non-fixed seasonality in time series

I believe some time series data I am looking at shows seasonality according to general elections (UK, so this can be 4 or 5 years). How do I remove this effect in R?
0
votes
0answers
29 views

ar.ols() or arima() for modeling time series

When trying to fit a AR(p) model to a time series in R, it seems that both ar.ols() and arima() will work. Is there some consideration of when to use which then? ar.ols() seems to use least square ...
0
votes
0answers
31 views

Question about trend and predictions in R

I have weekly data which I am considering as reference. So Mondays trend for example.. orders will kind of serve as valid data to make predictions for orders throughout the day for every Monday. I ...
0
votes
1answer
88 views

R time-series forecasting with neural network, auto.arima and ets

I've heard a bit about using neural networks to forecast time series. How can I compare, which method for forecasting my time-series (daily retail data) is better: auto.arima(x), ets(x) or ...
1
vote
0answers
46 views

ARIMAX for modelling daily sales

I am trying to model daily sales for a take out restaurant. They are only open on business days - no holidays or weekends - as their primary clients are office workers on their lunch breaks. Below is ...
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
0answers
114 views

Forecasting daily data with trend, yearly, day of the week, and moving holiday effects

I'm expanding a question I posed earlier because I think it was lacking detail. I'm attempting to forecast daily demand for a restaurant that sells take away food, primarily to office workers on ...
1
vote
1answer
177 views

Time series forecasting using R

I have many time series(retail data). Some with trends, some seasonal, and some with neither. With period day, week or month. I need to make forecast, for each time serie. I'm looking for the most ...
2
votes
1answer
65 views

Forecasting irregular time series (with R)

There are several methods to make forecasts of equidistant time series (e.g. Holt-Winters, ARIMA, ...). However I am currently working on the following irregular spaced data set, which has a varying ...
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 ...
1
vote
1answer
50 views

Warning message in auto.arima

I am using auto.arima() for prediction, and getting the following warning message. I want to know if I can ignore this warning message or if I should be worried. ...
4
votes
1answer
112 views

Time series prediction: visualising path uncertainty region

I am predicting a time series' future evolution and am evaluating the path uncertainty using bootstrapping. Is there a good way to visualise the uncertainty that goes beyond simply plotting a pair of ...
0
votes
0answers
21 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
0answers
63 views

Time series modeling with R on weekly data

I am trying to do time series modeling and forecasting using R based on weekly data like below - ...
2
votes
1answer
104 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 ...
1
vote
1answer
75 views

help on how to include term $\exp(β_t)/(1+\exp(β_t))$ in AR(2) model

I am trying to include a term in an AR(2) model: $$Y_t=\left( a_0+a_1 \frac{\exp(\beta_t)}{1+\exp(\beta_t)}\right)Y_{t-1}+bY_{t-2}+\delta\epsilon_t$$ Can anyone please help me with this? I don't seem ...
1
vote
1answer
45 views

ar() time series function in R, manually checking the residuals/predicted values

I am using the ar() function to fit an AR model to some data, and this object will return the in sample residuals. I also know the syntax for how to get the corresponding predicted values, but I want ...
0
votes
0answers
32 views

fpp forecasting using AWS ubuntu

Is the package fpp (or any of its previous incarnations like forecast) supported in Ubuntu 12.04 using AWS? It is the only package that R downloads but when you load the library it throws an error. ...
4
votes
2answers
188 views

R detect increasing/decreasing trend of time series

I have lots of time series with periods: day, week or month. With stl() function or with loess(x ~ y) I can see how trends of ...
1
vote
0answers
31 views

Clustering time-shifted sales time-series

I need to perform clustering and classification of time series of weekly sales of different products. My data are weekly sales of different products in differest areas (stores). The challenges on this ...
1
vote
1answer
68 views

How to get the true mean forecast using the Arima package with a Box-Cox transformation

In the Arima package, using a Box-Cox transformation give wrong results when later applied to the forecast method. For example, consider this data: ...