pooled time series cross section data

... short time series gene expression data, ” Bioinformatics, vol 21, supplement 1, pp i159–i168, 2005 [7] C D Giurcˇ neanu, I Tˇ bus, and J Astola, “Clustering time a a ¸ series gene expression data ... + + + + 70 Time (h) Figure 1: Log-normalised intensity versus time for 130 genes For each gene, the line joins the average value at each time point Vertical dashed lines indicate time points ... (normalized intensity) 2.5 1.5 1.5 0.5 0.5 0.5 0.5 0 0 20 40 60 Time (h) (a) 20 40 60 Time (h) (b) 20 40 60 Time (h) (c) 20 40 60 Time (h) (d) Figure 7: Representation of the smooth curves distributed...

Ngày tải lên: 22/06/2014, 19:20

... on this from the doctors Given an input time series, data analysis such as segmentation produces what we call a 'summary series' In our case, summary series contains intervals with similar trend ... pattern matching techniques to analyse raw data from the Dow Jones News service database SUMTIME-MOUSAM (Sripada et al, 2002) used segmentation of input weather data to determine intervals with similar ... Raw data contains a number of artifacts due to external events such as baby handling and blood sampling These artifacts need to be separated from the input data before summarizing The example data...

Ngày tải lên: 22/02/2014, 02:20

... with Traffic Data The data used in our experiments was taken from highway traffic sensors, called loop detectors, in the 37 Figure 6: Data Set: V274 Figure 7: Data Set: V287 Figure 8: Data Set: ... unit time In our data set the volume data was sampled at minute intervals, i.e the vehicle count was recorded at the end of a minute interval and the counter was reset to Each data set is a time ... this section we assume that the entire data set is collected before the analysis begins In section we consider the incremental case where change-point detection proceeds concurrently with data...

Ngày tải lên: 16/03/2014, 19:20

... types of data sets, such as cross- section, time series, cross- section over time and panel data This book introduces and discusses time series data analysis, and represents the first book of a series ... 570 571 Preface Time series data, growth, or change over time can be observed and recorded in all their biological and nonbiological aspects Therefore, the method of time series data analysis should ... based on trivariate time series 4.6 General system of equations 4.7 Seemingly causal models with dummy variables 4.7.1 Homogeneous time series models 4.7.2 Heterogeneous time series models 4.8...

Ngày tải lên: 30/03/2014, 04:21

... H B CP B C H X X R e B b R C b B C $GDG(Di($W(ƯfciăgD$lWDăpiq`Ô9fDfDf9$Ôjă9Ô DISCRETIZING TIME SERIES w b B V X B B e P B CP X R CT e b BT S S R V X R CT X F b R C 3tDă`ÔDAD(D(lAăhw9$GDfÔDc(dƯ$A9$G`9GÔ9$Ôb...

Ngày tải lên: 30/03/2014, 13:20

... temporal and spatial redundancy of data in order to compress communications have also been considered For instance, in [4], data captured by each sensor over a time interval are fitted by (cubic) ... 8, pp 2275–2285, 2004 [23] C Richard, J C M Bermudez, and P Honeine, “Online prediction of time series data with kernels,” IEEE Transactions on Signal Processing, vol 57, no 3, pp 1058–1067, 2009 ... spatial correlation of data into account has been recommended by numerous researchers See, for example, [12–14] where relation between the topology of the network and measurement data is studied In...

Ngày tải lên: 21/06/2014, 17:20

... original data The bootstrap methods have been used extensively for static data sets When applied to time- series data, an additional requirement is to maintain as much as possible the inherent time ... Tienda Luna et al Microarry Dynamic Bayesian network First order Markov process Time y1 (0) Gene Time Time Time · · · Time N y1 (1) y1 (2) ··· y1 (N) y1 (0) y1 (1) y1 (2) ··· y1 (N) y2 (0) y2 (1) ... limited data replicates are available and the sample size in each data set is small The question is then how to produce the perturbed data from the limited available data sets and at the same time...

Ngày tải lên: 22/06/2014, 19:20

... refer to sections throughout the book first by chapter number followed by section number and, sometimes, subsection number Therefore, Section 6.3 refers to Section in Chapter 6, and Section 13.8.3 ... general approaches to estimation, thereby attempting to cover all data configurations— including cross section, panel data, and time series in one framework, without giving special attention to any ... 18.5.2 Panel Data 18.5.3 Nonbinary Treatments 18.5.4 Multiple Treatments Problems 633 636 Count Data and Related Models Why Count Data Models? Poisson Regression Models with Cross Section Data 19.2.1...

Ngày tải lên: 06/07/2014, 08:20

... Analysis Data Structures In order to give proper treatment to modern cross section and panel data methods, we must choose a stochastic setting that is appropriate for the kinds of cross section ... the time series dimension can be entirely unrestricted As we will see, this approach is justified in panel data applications with many cross section observations spanning a relatively short time ... statement is obvious For panel data analysis, the asymptotics is as the cross section dimension gets large while the time series dimension is fixed 1.3 Some Examples In this section we provide two examples...

Ngày tải lên: 06/07/2014, 08:20

... xK given by definitions (2.39) and (2.40) Sometimes we will write a linear projection in error form, as in equations (2.41) and (2.42), but other times the notation (2.38) is more convenient It ... equation (2.5) In this case, the partial e¤ects of x1 and x2 both depend on x ¼ ðx1 ; x2 Þ Sometimes we are interested in a particular function of a partial e¤ect, such as an elasticity In the ... to x1 whenever logð yÞ and logðxj Þ are well defined Definition (2.10) is more general because sometimes it applies even when logð yÞ is not defined (We will need the general definition of an elasticity...

Ngày tải lên: 06/07/2014, 08:20

... Estimators and Test Statistics In this section, we apply the previous concepts to sequences of estimators Because estimators depend on the random outcomes of data, they are properly viewed as random ... asymptotic distribution of test statistics once the limiting distribution of an estimator is known; see Section 3.5 The continuity of g is not necessary in Lemma 3.6, but some restrictions are needed ... zN ! z p d and xN À zN ! 0, then xN ! z Lemma 3.7 is called the asymptotic equivalence lemma In Section 3.5.1 we discuss generally how Lemma 3.7 is used in econometrics We use the asymptotic equivalence...

Ngày tải lên: 06/07/2014, 08:20

... are often reported in applied cross- sectional work, especially when the sample size is large Sometimes they are reported along with the usual OLS standard errors; sometimes they are presented in ... might denote a marginal tax rate, but we can only obtain data on the average tax rate We will study the measurement error problem in Section 4.4 Simultaneity Simultaneity arises when at least ... be written in full matrix form as ðX XÞÀ1 X Y, where X is the N Â K data matrix of regressors with ith row xi and Y is the N Â data vector with ith element yi Under Assumption OLS.2, X X is nonsingular...

Ngày tải lên: 06/07/2014, 08:20

... K data matrices and Y is the N Â data vector on the yi The consistency of this estimator is immediate from equation (5.11) and the law of large numbers We consider a more general case in Section ... become clear later Sometimes for hypothesis testing we need to carry out the second-stage regression explicitly—see Section 5.2.4 The 2SLS estimator and the IV estimator from Section 5.1.1 are identical ... continuous, but sometimes xK , z1 , or both are discrete In fact, one or both of xK and z1 can be binary variables, or have continuous and discrete characteristics at the same time Equation (5.4)...

Ngày tải lên: 06/07/2014, 08:20

... samples In this section we briefly discuss some issues that arise for other sampling schemes that are sometimes assumed for cross section data 6.3.1 Pooled Cross Sections over Time A data structure ... pure cross section analysis can be applied to pooled cross sections, including corrections for heteroskedasticity, specification testing, instrumental variables, and so on But in using pooled cross ... individuals, firms, cities, and so on over time In a pooling of cross sections over time, there is no replicability over time (Or, if units appear in more than one time period, their recurrence is treated...

Ngày tải lên: 06/07/2014, 08:20

... Note on Time Series Persistence Theorem 7.7 imposes no restrictions on the time series persistence in the data fðxit ; yit Þ: t ¼ 1; 2; ; Tg In light of the explosion of work in time series ... any useful way 7.8 The Linear Panel Data Model, Revisited We now study the linear panel data model in more detail Having data over time for the same cross section units is useful for several ... we cannot with a single cross section A panel data set also allows us to control for unobserved cross section heterogeneity, but we will not exploit this feature of panel data until Chapter 10...

Ngày tải lên: 06/07/2014, 08:20

... di¤erent time periods for the same crosssectional unit (so G ¼ T, the total number of time periods) Therefore, the following analysis applies to panel data models where T is small relative to the cross ... between time periods that are far apart, as in the Newey and West (1987) estimator applied to time series problems Ziliak and Kniesner (1998) use a Newey-West type procedure in a panel data application ... general because it assumes that the underlying time series are weakly dependent (See Wooldridge, 1994, for discussion of weak dependence in time series contexts.) A Newey-West type estimator might...

Ngày tải lên: 06/07/2014, 08:20

... unity We maintain assumption (9.2) throughout this section and also assume that Eðz zÞ is nonsingular The notation here di¤ers from that in Section 9.2.1 Here, gg is G Â and dg is M Â for all ... B As we will touch on in Section 9.4.2, it is possible to put restrictions on S in order to identify B, but this approach is somewhat rare in practice Until we come to Section 9.4.2, S is an unrestricted ... economic theory implies parameter restrictions across di¤erent equations in a system that contains endogenous variables Not surprisingly, such cross equation restrictions are generally useful...

Ngày tải lên: 06/07/2014, 08:20

... first time period for each cross section: we now have T À time periods for each i, rather than T If we start with T ¼ 2, then, after differencing, we arrive at one time period for each cross section: ... increases; in time- series parlance, the vit are Basic Linear Unobserved E¤ects Panel Data Models 257 not weakly dependent across time (We show this fact explicitly in the next section when fuit ... modeling time- constant factors that are not of direct interest In panel data analysis the term ‘ time- varying explanatory variables’’ means that each element of x it varies over time for some cross section...

Ngày tải lên: 06/07/2014, 08:20

... solution to the measurement error problem with panel data that is not available with a single cross section or independently pooled à cross sections Under assumption (11.36), rit is uncorrelated ... repeated cross sections over time One simple data structure is a matched pairs sample To illustrate, we consider More Topics in Linear Unobserved E¤ects Models 329 the case of sibling data, which ... applied to equation (11.41) Therefore, xit cannot have time- constant variables or variables that have exact linear time trends for all cross section units 11.2.2 General Models with Individual-Specific...

Ngày tải lên: 06/07/2014, 08:20

... initially seem It covers cross section models with many equations, and it also covers panel data settings with small time series dimension The extension to independently pooled cross sections is almost ... in a variety of situations We will carry along the example of nonlinear least squares for cross section data to motivate the general approach In a nonlinear regression model, we have a random variable, ... Manski (1988, Section 4.2.4) Buchinsky (1994) applies quantile regression methods to examine factors a¤ecting the distribution of wages in the United States over time We end this section with...

Ngày tải lên: 06/07/2014, 08:20