Search results for "FD"
showing 10 items of 483 documents
"Table 3" of "First measurement of the quark to photon fragmentation function"
1995
2-jet events. Variable Z has been defined as E(gamma)/(E(gamma)+E(had)), where E(gamma) is the energy of the hard photon in 'photon-jet', E(had) is the energy of the rest hadrons in jet. Ycut is jet resolution parameter (see paper).
"Table 4" of "First measurement of the quark to photon fragmentation function"
1995
2-jet events. Variable Z has been defined as E(gamma)/(E(gamma)+E(had)), where E(gamma) is the energy of the hard photon in 'photon-jet', E(had) is the energy of the rest hadrons in jet. Ycut is jet resolution parameter (see paper).
"Table 1" of "First measurement of the quark to photon fragmentation function"
1995
2-jet events. Variable Z has been defined as E(gamma)/(E(gamma)+E(had)), where E(gamma) is the energy of the hard photon in 'photon-jet', E(had) is the energy of the rest hadrons in jet. Ycut is jet resolution parameter (see paper).
"Table 2" of "First measurement of the quark to photon fragmentation function"
1995
2-jet events. Variable Z has been defined as E(gamma)/(E(gamma)+E(had)), where E(gamma) is the energy of the hard photon in 'photon-jet', E(had) is the energy of the rest hadrons in jet. Ycut is jet resolution parameter (see paper).
"Table 5" of "First measurement of the quark to photon fragmentation function"
1995
3-JET events. Variable Z has been defined as E(gamma)/(E(gamma)+E(had)), where E(gamma) is the energy of the hard photon in 'photon-jet', E(had) is the energy of the rest hadrons in jet. Ycut is jet resolution parameter (see paper).
"Table 6" of "First measurement of the quark to photon fragmentation function"
1995
3-JET events. Variable Z has been defined as E(gamma)/(E(gamma)+E(had)), where E(gamma) is the energy of the hard photon in 'photon-jet', E(had) is the energy of the rest hadrons in jet. Ycut is jet resolution parameter (see paper).
"Table 7" of "First measurement of the quark to photon fragmentation function"
1995
3-JET events. Variable Z has been defined as E(gamma)/(E(gamma)+E(had)), where E(gamma) is the energy of the hard photon in 'photon-jet', E(had) is the energy of the rest hadrons in jet. Ycut is jet resolution parameter (see paper).
Filling in long gap sequences by performing jointly EOF and FDA
2012
In this paper the EOF methodology is performed jointly with the FDA approach on a spatiotemporal multivariate data set with the aim to fill in missing values as accurately as possible when long gap sequences occur. Simulated data sets, containing ”artificial” gaps, are considered in order to test the performance of two proposed procedures; in the first one, observed data are reconstructed by EOF and then converted into functional ones; in the second one, observed data are transformed into functional ones and then EOF reconstruction is applied. By comparing some performance indicators computed for the two procedures, it is shown that a pre-processing of data by FDA, followed by the EOF, may …
Long gaps in multivariate spatio-temporal data: an approach based on functional data analysis
2015
The main aim of this paper is to perform Functional Principal Component Analysis (FPCA) taking into account spatio-temporal correlation structures, in order to fill in missing values in spatio-temporal multivariate data set. A spatial and a spatio-temporal variant of the classical temporal FPCA is considered; in other words, FPCA is carried out after modeling data with respect to more than one dimension: space (long, lat) or space+time. Moreover, multidimensional FPCA is extended to multivariate context (more than one variable). Information on spatial or spatiotemporal structures are efficiently extracted by applying Generalized Additive Models (GAMs). Both simulation studies and some perfo…
Extending Functional kriging to a multivariate context
2020
Environmental data usually have a spatio-temporal structure; pollutant concentrations, for example, are recorded along time and space. Generalized Additive Models (GAMs) represent a suitable tool to model spatial and/or temporal trends of this kind of data, that can be treated as functional, although they are collected as discrete observations. Frequently, the attention is focused on the prediction of a single pollutant at an unmonitored site and, at this aim, we extend kriging for functional data to a multivariate context by exploiting the correlation with the other pollutants. In particular, we propose two procedures: the first one (FKED) combines the regression of a variable (pollutant),…