Questions tagged [time-series]
Time series are data observed over time (either in continuous time or at discrete time periods).
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Confusing multiple probability question
I'm trying something on time-series. I calculate the probability of a price movement in any given days. In this particular example here is what i have found:
...
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4 views
Prediction intervals of a logdiff time series when converting back to levels
I am having a problem when calculating prediction intervals of an ARIMA model of a logdiff transformed time series.
Assume I have the following point estimates for $h \in \{1, 2, 3\}$ where $y_{t+h}$...
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6 views
Align Two Pairs of Start and End Time Series Data
Overview
I have two data sets of (start,end) events:
Estimated Time series event pairs
Corrected Time series event pairs
The start and end points are seconds from the beginning of an event.
The ...
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7 views
Estimator of covariance in continuous time
In the discrete time (stationary) case, the covariance $R(\tau) = E\{(X_{t+\tau} - \mu)(X_{t} - \mu)\}$ can be estimated using
$\frac1n \sum\limits_{j=1}^{n-\tau} (x_{j+\tau}- \hat{\mu})(x_{j}- \hat{\...
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Reverse causality: Comparing two studies
I am writing a student-level essay (politics) and have encountered two interesting studies examining a similar variable: once as dependent and once as independet variable.
However:
(1) The first ...
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8 views
How can I find a representative point in 3D matrix (time,lon,lat)
I have temperature in a matrix of time, longitude and latitude. I need to find a way or criterion to find a point or location (lon *, lat *) that is representative of my entire area of interest (time, ...
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21 views
ARIMA forecast looks lagged
I am trying to make forecast of some time series that are both non-stationary and seasonal.
The overall result looks quite good. However, I constantly see a lag (or even a bias) between the observed ...
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1answer
18 views
Forecasting using Trend and seasonality
Im new here, also a newbie in statistics.
I was told to do forecasting at work by my boss.
I used to do a naive forecasting before, and i want that to change.
I want to do a real world forecast using ...
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11 views
Bilinear Process
how to generate a functional bilinear process such as:
$ X_{n+1}= \int\psi(t,s)X_{n}(s)ds + \iint\phi(t,s,u)X_{n}(s)\varepsilon_{n}(u)dsdu + \varepsilon_{n+1}(t) $ ?
About the first integral there ...
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1answer
31 views
What type of chart is this? A crossing stacked area chart?
The New York Times made some beautiful visualizations of energy consumption by state: link
What would this type of chart be called?
A cross-stacked area chart? Does anyone know any libraries or ...
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1answer
64 views
Daily data, R forecasts only yield straight line?
I've tried ets, tbats, and arima - I can't seem to get anything but a straight line out of this.
Example I tried:
...
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Should I use statistical inference on this “sample”?
The dataset gets its data from thousands of individuals throughout the US who update the same spreadsheet of about 5000 rows. This dataset contains address for individuals and is updated by the ...
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17 views
What is a good algorithm for multi-channel time series segmentation?
I have a high dimensional, multi-channel time series data set (70 trials of 273 channels by 1400 samples) and want to segment the data into 4-5 distinct underlying processes, extract those segments, ...
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7 views
model for short life cycle products using event detection
I would like to make predictions on short life cycle products.
I have a dataset with only 52 weeks.
The biggest problem of SLCPS is that it is impossible to find seasonality, cyclicity etc. etc.
I ...
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0answers
11 views
Which test should I use to predict a ratio from multilevel, time series data?
Thanks in advance for any help you can provide - I've done as much research as possible but I think it'll become obvious I'm somewhat unfamiliar with statistics.
Let's say that you've noticed that ...
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Why do we add $\delta_i \Delta Y_{t-i}$ in order to make an ADF test?
Let's say we have the ADF test for no constant and no deterministic trend. So the regression model is $$\Delta Y_t=\delta Y_{t-1}+\sum_{i=1}^{p-1} \delta_i \Delta Y_{t-i}+Z_t$$ according to https://en....
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What is local stationarity and how to detect it in time series
What is local stationarity time series and how to detect?
and what is the difference between it and between global stationarity?
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Linear Regression in my time series class [on hold]
I need help on creating sas code for a linear regression for electric consumption versus time in years from april 1997 to april 2018. A sample of my data is shown below in the images. I am using SAS. ...
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**Error in .cbind.ts(list(…), .makeNamesTs(…), dframe = FALSE, union = TRUE) : non-time series not of the correct length** [on hold]
Would you please help me to fix the R programming error?
...
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27 views
Linear Regression (Time series Analysis) [on hold]
How do I do a linear regression of electrical consumption against year (time) from the electrical data set for the years March 1997- March 2018. A sample of my data is shown below in the images. I am ...
1
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1answer
64 views
Correlation between two time series - volume and proportion
My company makes widgets. We take a random sample of these widgets every month and count how many are good and bad. Some people think that we are worse at making widgets in the months where we make ...
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20 views
How outliers influence your results? and what are good and bad leverage points?
I am confused between outliers and leverage points. And the difference between good and bad leverage points in time series analysis.
Can somebody help me?
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what are cross correlations and why these cross correlations provide spurious results if two series are integrated?
I am much confused in CCF and how these provide Spurious results and why? Can any one help me. I'll be much thankful.
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How to compare two sets of time dependent proportions?
I am doing a sentiment analysis task about the people's attitudes towards transportation services in Hong Kong. I collected Tweets near the railway stations and see if there is any difference between ...
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11 views
how to write ARIMA(1 1 0)×(1 1 1)12? [duplicate]
I m not able to make pattern of this model. I want to write it in terms of y and e. Not in back shift opertor. plzz someone help me to do that
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1answer
30 views
Maximum number of Fourier terms in forecast package
I am using the forecast package in R to get some Fourier components - namely, function fourier(ts, K, ..). For a time series <...
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1answer
13 views
Normalizing value using 3 points / levels
I am using following formula to normalize number:
new = ((current - low) / (high - low)) * 100
But i need middle number to be the mode of the data. So in this ...
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2answers
49 views
Do these standardized residuals show heteroskedasticity?
I'm practising in the individuation of heteroskedasticity from the standardized residuals.
I know that, if the time series is homoskedastic, the spread of the residuals should be constant and random ...
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1answer
12 views
Moving Average Representation of a Stationary Time Series
I was wondering if this equation is considered a Moving Average process of order 13? If so, does that mean that the coefficients at times t-2 to t-11 are 0? As they are clearly not present in this ...
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0answers
19 views
Is my interpretation correct for these residuals plots?
In preparation for my exam, I'm trying to interpret the residuals in order to understand if the time series has been modelled correctly. Otherwise, I have to suggest an improvement.
Here is the text:
...
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ARIMA (2,1,0) = ARI(2,1) Please [on hold]
Prediction
ARIMA model (2,1,0)= ARI (2,1)
$(1−ϕ_1L−ϕ_2L^2)(1−L)Y_t=α+ϵ_t,\, ϵ_t\sim\text{iid}(0,\sigma^2_ϵ)$
1) Obtain the point predictions of $W_t=(1−L)Y_t$
2) Obtain the point predictions of $...
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Demand Estimation without data [closed]
I have a very interesting problem. Our client, a major theme park company wants to set up a park in an asian city. They want to a) understand the total demand to the park every week for the future ...
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1answer
26 views
Expectation, variance and autocorrelation of a “complex” AR(1) function
I'm preparing the exam for "stochastic models" and I encountered this exercise which is giving me a lot of problems:
Let
$$X_t=\phi X_{t-1}+\epsilon_t, ~~~~~~~~~~\epsilon_t \sim WN(0, \sigma^2)$$
...
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20 views
Example: multivariate timeseries model that is uncorrelated at each time step but has higher order interactions
What are examples of timeseries models, say $X_t = [X^{(1)}_t, X^{(2)}_t]^\top, t \in \mathbb{Z}$ (or potentially continuous time), such that they are time-wise uncorrelated, that is $\mathrm{cov}[X^{(...
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Specific data formatting techniques for discontiguous time series? [on hold]
I'm facing a predicting problem for food alerts. The goal is to predict the variables of the most probable alert in the next x days (also any information I could get about future alerts is really ...
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Arima forecasting on dataset with many 0s
I have a dataset which contains 30 0 values out of a total of 80 observations. Is there a good technique to fit an ARIMA model on the data without either removing the 0 values or performing a moving ...
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27 views
How to choose between additive and multiplicative decomposition in time series
I have a time series which is the number of weekly flu cases from 2010 to early 2018 in one county. I want to remove seasonality from my data so I can have a clearer data to infer the relationship ...
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2answers
54 views
Proof expression for the autocovariance function of AR(1)
The representation for the model AR(1) is the following:
$Y_t=c+ϕY_{t-1}+ε_t$
where $c=(1-ϕ)μ$ ($c$ is a constant).
I want to understand the calculations that there are behind the general formula ...
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Average time series forecast errors from cross-validation with rolling origin
I'm calculating the MAPE and RMSE over a rolling origin cross-validation with fixed forecast interval for several models. For example, for a daily series with 3 years, I'm training my model with 2 ...
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7 views
Is it mandatory to supply expected values using SARIMA in python?
I went through several examples on the internet discussing time series models. All of them take the dataset, divide it into train and test subsets, then make predictions. On those lines, I have built ...
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1answer
32 views
Predictability of a time series
Say we are given a time series $(x_t)_{t \in P}$ where $P$ is the index set of past observations (train set).
Imagine that we have built a model for our data and now want to assess predictability of ...
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12 views
Comparing two groups of time series correlation coefficients?
I have two groups of data, each consisting of 100 correlation coefficients.
I am interested in essentially seeing if the correlations in group 1 are stronger than group 2. However, I am unsure of the ...
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0answers
6 views
Steps required for time series data empirical analysis
I have four variables e.g gdp as dependent variable while fdi, trade epenness and official development assistance as independent variables of 38 years. I am going to analyse data empirically. So guide ...
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2answers
38 views
Non stationary model applied to stationary data
If the model is non stationary, can it be applied to stationary data/series?
For example the KPSS test shows that the data is stationary but the BP test shows presence of heteroscedasticity.
If a ...
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19 views
Let $y_t$ be a process satisfying $y_t=\alpha+\beta t+\eta_t$ and $\eta_t=\phi\eta_{t-1}+\epsilon_t$.To model $y_t$ under different cases
$y_t=\alpha+\beta t+\eta_t$ and $\eta_t=\phi\eta_{t-1}+\epsilon_t$
Given that $\epsilon_t\sim WN(0,\sigma_\epsilon^2))$.
What would you do for modeling $y_t$ in the following cases?
$\phi=1$.
$|\...
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Verify if $y_t=\phi y_{t-1}+\epsilon_t$ is second order stationary
Here$\;\{\epsilon_t\}\;$is a sequence of identically distributed Student t random variables with d.f.=2. Is this process second order stationary?
I am confused since $\;Var(\epsilon_t)\;$ tends to ...
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31 views
When using a time series training set, do you consider the same object at different times as 2 separate objects?
Let's say I have a stock that I own and the value of that stock over 4 days. I also know if the stock on that day falls into one of 2 categories. On each day I want to make a feature out of the ...
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0answers
14 views
MA Residuals in R using arima()
I fit a MA(1) model using arima() in R:
set.seed(100)
y = arima.sim(list(ma=c(-.6)),n=100)
fit=arima(y, order=c(0,0,1), include.mean = FALSE)
The model being fit ...
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0answers
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How to incorporate uncertainty and noise information in training and prediction of neural networks?
I am trying to use RNNs to perform state estimation on noisy sensor data. The readings are from a GPS dataset and it provides $[longitude, latitude, n_{satellites}]$. The last column, which is the ...
