Testing copula regression against benchmark models for point and interval estimation of tree wood volume in beech stands

Serinaldi, Francesco; Grimaldi, Salvatore; Abdolhosseini, Mohammad; Corona, Piermaria; Cimini, Dora

doi:10.1007/s10342-012-0600-2

Cited by 15 publications

(12 citation statements)

References 47 publications

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“…The MLR and EXP models were fitted to the original data. Table 6 shows the results for some commonly used performance criteria (e.g., [69]) and the summary statistics for the estimated SSL values using the copula model. For MLR and EXP models original data (autocorrelation in the Q data was not removed) was used.…”

Section: Comparison With Other Ssl Estimation Techniquesmentioning

confidence: 99%

“…Figure 6 shows diagnostic plots for the three compared models, while some commonly used performance criteria are presented in Table 3. According to the different performance criteria [69], the proposed copula model yields the worst fit among the tested models. However, the diagnostic plots ( Figure 6) demonstrate that the residuals are generally the smallest when using the copula model.…”

Section: Comparison With Other Ssl Estimation Techniques and Estimatimentioning

confidence: 99%

“…Several performance criteria described by [69] such as Mean absolute error (MAE), Root mean square error The methodology presented in Section 2 for the estimation of the SSL values based on the measured Q and P was tested using the high-frequency data measured in the Kuzlovec torrent. The IEs value of 6 h was selected for the Kuzlovec torrent.…”

Section: Regression Models and Performance Criteriamentioning

confidence: 99%

“…The adequacy of the selected distribution function was tested using the Cramér-von Mises test that is implemented in the program R lmomco package [67]. Additionally, the following nonparametric distribution function was used for the Gornja Radgona on the Mura River case study due to the larger number of analysed events [68,69]:…”

Section: Copula Functionmentioning

confidence: 99%

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Estimation of Suspended Sediment Loads Using Copula Functions

Bezak

Rusjan

Fijavž

et al. 2017

Water

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Suspended sediment load (SSL) observations are usually less frequent than precipitation and river discharge measurements; therefore a reliable procedure is needed for the estimation of SSL. One year of precipitation, SSL, and discharge measurements at 20-min intervals were performed at the Kuzlovec torrent in Slovenia. The Frank copula was selected to construct an event-based model using the following variables: precipitation sum (P), peak discharge (Q), and SSL. The idea was to estimate the SSL based on the measured P and Q. The proposed model was additionally tested using the daily data from the Gornja Radgona station on the Mura River, for which 29 years of data were available and where Khoudraji-Liebscher copulas were used. The estimated SSL values using the copula were compared with different regression models. The proposed copula model yielded meaningful SSL estimates. Some performance criteria and tests indicated that the copula model gives a better fit to the measured data than other tested methods.

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Section: Comparison With Other Ssl Estimation Techniquesmentioning

confidence: 99%

Section: Comparison With Other Ssl Estimation Techniques and Estimatimentioning

confidence: 99%

Section: Regression Models and Performance Criteriamentioning

confidence: 99%

Section: Copula Functionmentioning

confidence: 99%

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Estimation of Suspended Sediment Loads Using Copula Functions

Bezak

Rusjan

Fijavž

et al. 2017

Water

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“…It should be emphasized that OLS has five assumptions (Helsel and Hirsch, 2002): y and x are linearly dependent; the data used to fit the model are representative; the variance of the residuals is constant; and the residuals are independent and normally distributed. If the assessment of uncertainty or confidence intervals is of concern, statistical hypothesis should be introduced (Serinaldi, et al, 2012). In this case, the last three assumptions must be fulfilled.…”

Section: Ordinary Least Squares (Ols) Regressionmentioning

confidence: 99%

Record extension for short-gauged water quality parameters using a newly proposed robust version of the Line of Organic Correlation technique

Khalil

Adamowski

2012

Hydrol. Earth Syst. Sci.

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Abstract. In many situations the extension of hydrological or water quality time series at short-gauged stations is required. Ordinary least squares regression (OLS) of any hydrological or water quality variable is a traditional and commonly used record extension technique. However, OLS tends to underestimate the variance in the extended records, which leads to underestimation of high percentiles and overestimation of low percentiles, given that the data are normally distributed. The development of the line of organic correlation (LOC) technique is aimed at correcting this bias. On the other hand, the Kendall-Theil robust line (KTRL) method has been proposed as an analogue of OLS with the advantage of being robust in the presence of outliers. Given that water quality data are characterised by the presence of outliers, positive skewness and non-normal distribution of data, a robust record extension technique is more appropriate. In this paper, four record-extension techniques are described, and their properties are explored. These techniques are OLS, LOC, KTRL and a new technique proposed in this paper, the robust line of organic correlation technique (RLOC). RLOC includes the advantage of the LOC in reducing the bias in estimating the variance, but at the same time it is also robust in the presence of outliers. A Monte Carlo study and empirical experiment were conducted to examine the four techniques for the accuracy and precision of the estimate of statistical moments and over the full range of percentiles. Results of the Monte Carlo study showed that the OLS and KTRL techniques have serious deficiencies as record-extension techniques, while the LOC and RLOC techniques are nearly similar. However, RLOC outperforms OLS, KTRL and LOC when using real water quality records.

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Antecedent Moisture Condition (Scs) Frequency Assessment: A Case Study in Southern Italy

Paola

Ranucci

Feo³

2013

Irrigation and Drainage

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This paper reports on a procedure used to define the joint probability distribution of two hydrological variables describing a meteoric event: the maximum intensity of the rain and the accumulation in the antecedent five days. The main goal is to define the frequency of occurrence of the three antecedent moisture condition classes of the SCS-CN method connected to extreme intensity rain events, with reference to a very precise data set containing records with aggregation time of 10 min. In order to define the relation between the hydrological variables, the marginal distribution of the two variables was first identified and afterwards the global dependency structure was studied through the copula function.Afterwards, according to data collected from rain gauge stations located in the Campania region, in southern Italy, and selecting peak-intensity rain events higher than 20 mm h -1 , the evidence was that the AMCI class is the most frequent, rather than the AMCIII class (the frequency of which is never above 26% in the vegetal dormant season and 12% in the vegetal growing season).Such results lead to the conclusion that using the AMCIII class in design calculation, mainly in dry areas (like southern Italian regions), is not particularly suitable, while the use of AMCII is more advisable. RÉSUMÉCet article présente la procédure utilisée pour définir la distribution de la probabilité conjointe de deux variables hydrogéologiques qui décrivent un événement météorologique: l'intensité maximum de la pluie (i) et la pluie accumulée pendant les cinq jours précédents (cum 5). L'objectif principal est de définir la fréquence d'événements des trois classes de conditions d'humidité antécédentes en relation avec les événements pluvieux d'extrême intensité, en se référant à un jeu de données très précises agrégées au pas de temps de 10 minutes.A priori pour définir la relation entre les variables hydrogéologiques nous avons identifié la distribution marginale des deux variables puis étudié la structure de dépendance globale à travers la fonction copula.En accord avec une analyse de sensibilité développée en fixant une typologie, en utilisant une variable sol et faisant virier la classe AMC, il était possible d'établir que la classe AMCIII amène à des valeurs des volumes hydriques plutôt élevés (deux à trois fois plus par rapport à ceux fournis par l'AMCII).Ensuite, en accord avec les données recueillies par des stations pluviométriques dans la région de la Campanie, dans le sud de l'Italie et en sélectionnant les événements avec un pic supérieur à 20 mm h -1 , on est arrivé à la conclusion que la classe AMCI est la plus fréquente (aussi par rapport à la classe AMCIII dont la fréquence ne dépasse jamais les 26% de la période de repos végétatif ou les 12% en période de développement des végétaux).Ces résultats nous ont permis de conclure que l'utilisation de la classe AMCIII n'est pas tout à fait adaptée aux résultats attendus, surtout dans des endroits arides comme le sud de l'Italie. Pourtant on conseille l'utilisation de l'AM...

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Testing copula regression against benchmark models for point and interval estimation of tree wood volume in beech stands

Cited by 15 publications

References 47 publications

Estimation of Suspended Sediment Loads Using Copula Functions

Estimation of Suspended Sediment Loads Using Copula Functions

Record extension for short-gauged water quality parameters using a newly proposed robust version of the Line of Organic Correlation technique

Antecedent Moisture Condition (Scs) Frequency Assessment: A Case Study in Southern Italy

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