Time series are data observed over time (either in continuous time or at discrete time periods).
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271 views
How to check which model is better in state space time series analysis?
I am doing time series data analysis by state space methods. With my data the stochastic local level model totally outperformed the deterministic one. But the deterministic level and slope model gives ...
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86 views
Irregularly spaced time-series in finance/economics research
In financial econometrics research, it is very common to investigate relationships between financial time series that take the form of daily data. The variable will often be made $I(0)$ by taking the ...
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131 views
$ARIMA(p,d,q)+X_t$, Simulation over Forecasting period
I have time series data and I used an $ARIMA(p,d,q)+X_t$ as the model to fit the data. The $X_t$ is an indicator random variable that is either 0 (when I don’t see a rare event) or 1 (when I see the ...
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157 views
Finding the correct data mining approach
(I apologise for being a newb, but I'm a researcher introducing myself to data mining---any help or insight would be greatly appreciated. Also, this isn't technically a homework question, but I've ...
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196 views
Dynamic factor analysis vs factor analysis on differences
I'm trying to wrap my head around dynamic factor analysis. So far, my understanding is that DFA is just factor analysis plus a time series model on the scores (the loadings remain fixed). However, in ...
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127 views
Examining correlation and long range dependence in time series data with strong diurnal effects
I have data sets of network traffic that exhibit strong diurnal effects making them non-stationary. One of the analysis that I want to run is to show correlation between days. If we chopped up the ...
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298 views
Measure score change over time while accounting for baseline differences
I'd like to test for and estimate group differences in NIHSS (National Institute of Health Stroke Scale) change between hospital discharge and three months after hospital discharge.
Because the score ...
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141 views
Updating classification probability in logistic regression through time
I am building a predictive model that forecasts a student's probability of success at the end of a term. I’m specifically interested in whether the student succeeds or fails, where success is usually ...
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356 views
Exogenous variables in VECM
I found the following posts interesting and I was wondering if any of you guys know of good academic papers that describe methods/relationships of exogenous variables in VECM models. If so could you ...
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80 views
How to design good plots for multiple time series?
I have huge (about 100 000) set of time series. I need to show between 5 to 10 time series, chosen semi-randomly on one chart. Chart estate is very limited - plot for each time series is only 100px x ...
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144 views
Stationarity tests for time series
I am currently working on time series modeling, especially on stationarity tests. For this purpose, I am extensively using Pfaff's book "Analysis of integrated and cointegrated time series with R" and ...
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100 views
Relationship between LASSO T and LARS number of steps k
We can see on the figure (cf Least Angle Regression p30, Efron, Hastie, Johnstone, Tibshirani - link: Least Angle Regression) that there is a direct relationship between:
LASSO T absolute norm of ...
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113 views
Mixed model vs. Pooling Standard Errors for Multi-site Studies
I've got a data set consisting of a series of "broken stick" monthly case counts from a handful of sites. I'm trying to get a single summary estimate from two different techniques:
Technique 1: Fit a ...
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115 views
Estimating parameters of an unknown PID controller
Say that I have your standard PID controller at work. To keep it extremely simple imagine I have a target $x^*$ on the variable $x$. Then the controller is:
$y(t) = K_p ( x^* - x_t) + K_i \int_0^t ...
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40 views
Estimating a time frame for interventions or judging the extent to which events become “determined” as time goes on
In certain arenas, it's valuable to be able to intervene early on to prevent problems from getting worse, because after a certain point there's not much you can do. Two examples might be public health ...
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243 views
Simulating time-series given power and cross spectral densities
I am having trouble generating a set of stationary colored time-series, given the covariance matrix (their PSDs and CSDs).
I know that, given two time-series $y_{I}(t)$ and $y_{J}(t)$, I can ...
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108 views
What's the probability a rabbit will return to a (certain) forest?
Let's assume we have a forest.
And there is a breed of rabbits that is visiting that forest all the time.
It is possible to distinguish every individual rabbit.
There are devices in that forest ...
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237 views
Asynchronous (irregular) Time Series Analysis
I am trying to analyze the lead-lag between time series of two stock prices.
In regular time series analysis, we can do Cross Correlaton, VECM (Granger Causality). However how does one handle the ...
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225 views
How does pooling and resampling affect variance of sample mean?
Suppose I have $N$ independent random variables $X_n$. I draw a sample of predetermined size $K_n$ from each of them. Denote the average of each sample $\bar{\hat{X}}_n$, and the total number of ...
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259 views
How to model time-varying correlation
Suppose I have two time-series variables, $\{x_t\}$ and $\{y_t\}$, where $t\in[1,T]$. I would like to model the correlation $\rho(x_t,y_s)$ as some function of $t$,$s$, and the difference $t-s$. In ...
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40 views
Link Anomaly Detection in Temporal Network
I came across this paper that uses link anomaly detection to predict trending topics, and I found it incredibly intriguing: The paper is "Discovering Emerging Topics in Social Streams via Link Anomaly ...
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34 views
How to form a confidence band around the trend fitted from time series data
I have a time series data set. I can decompose it and get the trend but I would like to put confidence ranges around the trend (past) not the forecast-ed component. The decompose function also ...
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93 views
What is the best test for validating trends in time-series data?
I have annual temperature data from a variety of weather stations in the Caribbean and I want to be able to show statistically that the trends for each station are significant, either positive or ...
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52 views
T-test when observations are years
I would like to know whether I can use the t-test or the non-parametric equivalent test when I have years as observations. Suppose I want to compare the profitability levels of two companies and I ...
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72 views
Prediction model problem
I am trying to design a model that can estimate the number of customers I will receive in every store every month using the number of customers I received every month in every store for the last five ...
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37 views
What type of tool/statistic should I use to inspect two misaligned time series of different granularity?
I have two separate time series, indexed by time in nanoseconds. They both measure the same thing but because they come about in two completely different ways, the number of observations they each ...
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47 views
Way to rank binary sequence
Bear with me as I try to word this question well (I'm a mathematical modeler, but not a statistics guru).
We want to assess the response patterns of a binary timeseries. The data are from people ...
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436 views
Time series forecasting using autoregressive and linear terms in R
I have real daily market data which I'm looking at to create a model for forecasting. The model that I created (below) used autoregressive terms within a linear regression.
I was sharing this with a ...
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238 views
Hidden Markov models and anomaly detection
In Shane's answer to this question he suggests that Hidden Markov Models can be used more successfully than wavelets for anomaly / change detection (it was a bit unclear -the topic he was addressing ...
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262 views
Lag length selection Granger causality test
Consider G-Causality on two stationary time series vectors (call these variables $X$ and $Y$), each with 100+ observations. It's daily financial market time series data. I have reason to believe that ...
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123 views
Clustering & Time Series
I have a multivariate dataset that changes over time. I have extracted (and normalised) some features and used k-means to generate clusters over the entire span of the dataset.
Now I want to see ...
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107 views
Forecasting a complex time series by splitting into subseries
I have finance data that I need to forecast out for 7 years. My data is generally debits and credits, and those are split into a number of sub-series which share common traits (e.g. similar ...
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145 views
Time Series: correcting the standard errors in a huge panel time series data set
I have stock returns at every 5 minute interval of each trading day for over 2 years for 40 stocks. I want to run a Fama-Macbeth regression by time interval (5min intervals) and then correct the ...
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32 views
How to find 1-year population average with intermittent series data
I have performance review data and scores (ranging from 1 to 4) for employees of a company. I need to show the company average over the past year. However, the employees were only ever reviewed for a ...
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138 views
How to combine several time series into a useful average time series?
Let's assume we have four time series a, b, c and d with 10 measurments.
a(1), ..., a(10)
b(1), ..., b(10)
c(1), ..., c(10)
d(1), ..., d(10)
a, b and c are ...
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80 views
Time series modeling the number of users of a mobile app
I want to model the number of users of an mobile app. This app has two kinds of users: free and paid. I thought of this autoregressive model:
$x_t = Ax_{t-1}$
with $x_t$ being a 4-dimensional ...
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115 views
How to implement a two-stage hierarchical model of time series data in R?
I'm currently working with a data set that consists of a monthly case count for several sites, along with a number of site-specific covariates. We're trying to estimate the effect of one of them on ...
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131 views
Comparing principal components if number of variables changes
I have a database that contains daily stock returns of more than a thousand stocks for many decades. I would like to achieve the following goals:
Construct a time-varying measure of co-movement (or ...
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132 views
Least stupid way to forecast a short multivariate time series
I need to forecast the following 4 variables for the 29th unit of time. I have roughly 2 years worth of historical data, where 1 and 14 and 27 are all the same period (or time of year). In the end, I ...
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88 views
How to tell if data is filtered well?
I have about 3 hours worth of 3-axis accelerometer, gyroscope and compass data taken at subsecond intervals. I'm fully aware that this data needs to be filtered and that there are a shedload of ...
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117 views
Comparing models of discrete and continuous data
I have a data-analysis problem with two closely-related timeseries. Both are binned in time at the same rate, but one is discrete (takes values in $\mathbb{Z}$), and the other is continuous. I am ...
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170 views
Is is possible (or advisable) to do Change Point Analysis on sequence of groups with R?
I'm familiar with post-hoc testing with ANOVA for exploring differences between a sequence of groups, but recently I've been reading about Change Point Analysis ...
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120 views
Testing for the existence of dependencies in time series
What methods exist to test for the existence of any sort of dependence in a time series? This is in contrast to something like auto-correlation, which tests for a particular type of dependency. Is ...
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71 views
Confidence intervals for difference in time series
I have a stochastic model used to simulate time series of some process. I am interested in the effect of changing one parameter to a specific value and want to show the difference between the time ...
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64 views
Theoretical corrections of the training error for time series data
With $y_1, \ldots, y_n$ a real valued time series and $\hat{f} : \mathbb{R} \to \mathbb{R}$ a (least square) estimate of the function $y \mapsto E(Y_i \mid Y_{i-1} = y)$ the training error
...
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96 views
How to denoise a “Poissonous” time series
I have $N$ time series each of which can be modeled as $$y_{kt}=Ax_{kt}+b+\varepsilon_{kt}\quad(1\le k\le N,1\le t\le T),$$ where $x_{kt}\sim\text{Pois}(\lambda\Delta t)$ and $\varepsilon_{kt}\sim ...
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638 views
Fitting the moving average model
let v to be forecasted value for periods 1 through T and $v_{t}$ be its forecasted value at time $t$. We express $v_{t}$ as the sum of two terms, its mean at time $t$, and its deviation from the ...
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43 views
Best practices for dealing with shifting, inconsistent seasonality
This question is related to a previous post I've looked at (Calculation of seasonality indexes for complex seasonality), but deals with more granular data (daily instead of weekly), and transforming ...
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38 views
Dummy variables for time series
I'm a new user on R. I'm stuck on my times series research currently with the some questions. Not sure anyone can help me.
Dummy variable.
I wanted to add more than 1 dummy variable in the model. ...
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37 views
Time Series Analysis (ARIMA) with Logistic Regression and Control variables
I'm planning to do a study on readmissions in a certain hospital unit and I want to study the impact of an intervention on readmission rate (binary variable), while controlling for individual-level ...
