E. Guagenti - Academia.edu (original) (raw)

Papers by E. Guagenti

Research paper thumbnail of A proposal for comparing the reliabilities of alternative seismic hazard models

Differences between statistical unertainty and modeling uncertainty are briefly discussed. It is ... more Differences between statistical unertainty and modeling uncertainty are briefly discussed. It is pointed out that, when different models are proposed for the interpretation of reality, the uncertainty cannot be described in terms of mean value and coefficient of variation. The important question is: which of the proposed models is more reliable than the others?

Research paper thumbnail of Inferences on the main volcano-tectonic structures at Mt. Etna (Sicily) from a probabilistic seismological approach by S. Gresta, L. Peruzza, D. Slejko and G. Distefano...................................... 105–116 Verification and refinement of spectral magnitude calibrating functions for P-wave...

Research paper thumbnail of Short-Term Precursors of Natural Disastrous Events: A Statistical Assessment

IAVCEI Proceedings in Volcanology, 1992

Research paper thumbnail of Semi-Markov processes in seismic risk analysis

Research paper thumbnail of A dynamic system approach to structural rehabilitation planning

Mechanics Research Communications, 1981

Research paper thumbnail of Earthquake catalogues and modelling strategies. A new testing procedure for the comparison between competing models

Journal of Seismology, 2006

In this paper we consider the procedures that, on the basis of an earthquake catalogue, yield the... more In this paper we consider the procedures that, on the basis of an earthquake catalogue, yield the magnitude distribution function F M (F M generators). In particular, our attention is focused on the F M generators that are currently used in the frame of the probabilistic seismic hazard analysis at a site. From an engineering point of view, the behaviour of F M in the range of strong earthquakes is of crucial importance. On the other hand, in general, the statistical validation of F M in that range is not feasible because of an insufficient number of strong earthquakes in available catalogues.

Research paper thumbnail of Renewal models for earthquake predictability

Journal of Seismology, 2010

The new Database of Italy's Seismogenic Sources ) identifies areas with a degree of homogeneity i... more The new Database of Italy's Seismogenic Sources ) identifies areas with a degree of homogeneity in earthquake generation mechanism judged sufficiently high. Nevertheless, their seismic sequences show rather long and regular interoccurrence times mixed with irregularly distributed short interoccurrence times. Accordingly, the following question could naturally arise: do sequences consist of nearly periodic events perturbed by a kind of noise; are they Poissonian; or short interoccurrence times predominate like in a cluster model? The relative reliability of these hypotheses is at present Electronic supplementary material The online version of this article (

Research paper thumbnail of Seismic risk analysis with predictable models

Earthquake Engineering & Structural Dynamics, 1988

Research paper thumbnail of Some observations on the probabilistic interpretation of short-term earthquake precursors

Earthquake Engineering & Structural Dynamics, 1984

This paper analyses the uncertainties in probabilistic interpretation of short-term earthquake pr... more This paper analyses the uncertainties in probabilistic interpretation of short-term earthquake precursors, even when the statistical information commonly indicated in the literature as sufficient to define the characteristics of these precursors is assumed to be known. The wide margins for uncertainty in the interpretation of such data are pointed out. One of the principal causes of uncertainty, as an example, lies in the physical origin of false alarms. Depending on this physical origin, the conditional probability of an earthquake, other conditions being equal, may vary in certain cases from values around 0.1 to as much as 0.7 or even higher.

Research paper thumbnail of Seismic hazard analysis: How to measure uncertainty?

Computers & Structures, 1998

Applications of probabilistic seismic hazard analysis demand the adoption of a model (i.e. of the... more Applications of probabilistic seismic hazard analysis demand the adoption of a model (i.e. of the forms of a certain number of correlations and probabilistic distributions) and the estimate of the parameters of the model. As a measure of uncertainty in the calculation of the expected value of a given quantity (for instance the peak ground acceleration corresponding to a given return period at a given site) a coecient of variation is frequently adopted, which is intended to include uncertainties due to both the choice of the model and the estimate of parameters. The following three statements are illustrated in this paper: (1) in theory, the use of a coecient of variation, when uncertainties in modeling are involved, is not correct, (2) in practice, the aforesaid use can lead to unreliable results and (3) the analysis of uncertainties can be carried out in a more satisfactory way if uncertainties in modeling and uncertainties in the estimate of parameters are considered separately and with dierent approaches. #

Research paper thumbnail of Statistical Grounds for Favoring the Characteristic Magnitude Model: A Case Study

Bulletin of the Seismological Society of America, 2008

Research paper thumbnail of A proposito di validazione

When a hazard quantity a concerning rare events has to be estimated, the estimated value ais affe... more When a hazard quantity a concerning rare events has to be estimated, the estimated value ais affected by a very large uncertainty. The background hypothesis cannot be validated in an absolute sense: the physical knowledge of rare events is weak; the classic statistical analysis assigns equivalent degree of acceptance to different hypotheses; no direct quantitative evidence can be derived from the poor data set. Here a relative cryterium of validation is used based on an index that measures the variability of estimated quantity; only two competing models are taken in consideration and judged on the basis of the above index.

Research paper thumbnail of A proposal for comparing the reliabilities of alternative seismic hazard models

Differences between statistical unertainty and modeling uncertainty are briefly discussed. It is ... more Differences between statistical unertainty and modeling uncertainty are briefly discussed. It is pointed out that, when different models are proposed for the interpretation of reality, the uncertainty cannot be described in terms of mean value and coefficient of variation. The important question is: which of the proposed models is more reliable than the others?

Research paper thumbnail of Inferences on the main volcano-tectonic structures at Mt. Etna (Sicily) from a probabilistic seismological approach by S. Gresta, L. Peruzza, D. Slejko and G. Distefano...................................... 105–116 Verification and refinement of spectral magnitude calibrating functions for P-wave...

Research paper thumbnail of Short-Term Precursors of Natural Disastrous Events: A Statistical Assessment

IAVCEI Proceedings in Volcanology, 1992

Research paper thumbnail of Semi-Markov processes in seismic risk analysis

Research paper thumbnail of A dynamic system approach to structural rehabilitation planning

Mechanics Research Communications, 1981

Research paper thumbnail of Earthquake catalogues and modelling strategies. A new testing procedure for the comparison between competing models

Journal of Seismology, 2006

In this paper we consider the procedures that, on the basis of an earthquake catalogue, yield the... more In this paper we consider the procedures that, on the basis of an earthquake catalogue, yield the magnitude distribution function F M (F M generators). In particular, our attention is focused on the F M generators that are currently used in the frame of the probabilistic seismic hazard analysis at a site. From an engineering point of view, the behaviour of F M in the range of strong earthquakes is of crucial importance. On the other hand, in general, the statistical validation of F M in that range is not feasible because of an insufficient number of strong earthquakes in available catalogues.

Research paper thumbnail of Renewal models for earthquake predictability

Journal of Seismology, 2010

The new Database of Italy's Seismogenic Sources ) identifies areas with a degree of homogeneity i... more The new Database of Italy's Seismogenic Sources ) identifies areas with a degree of homogeneity in earthquake generation mechanism judged sufficiently high. Nevertheless, their seismic sequences show rather long and regular interoccurrence times mixed with irregularly distributed short interoccurrence times. Accordingly, the following question could naturally arise: do sequences consist of nearly periodic events perturbed by a kind of noise; are they Poissonian; or short interoccurrence times predominate like in a cluster model? The relative reliability of these hypotheses is at present Electronic supplementary material The online version of this article (

Research paper thumbnail of Seismic risk analysis with predictable models

Earthquake Engineering & Structural Dynamics, 1988

Research paper thumbnail of Some observations on the probabilistic interpretation of short-term earthquake precursors

Earthquake Engineering & Structural Dynamics, 1984

This paper analyses the uncertainties in probabilistic interpretation of short-term earthquake pr... more This paper analyses the uncertainties in probabilistic interpretation of short-term earthquake precursors, even when the statistical information commonly indicated in the literature as sufficient to define the characteristics of these precursors is assumed to be known. The wide margins for uncertainty in the interpretation of such data are pointed out. One of the principal causes of uncertainty, as an example, lies in the physical origin of false alarms. Depending on this physical origin, the conditional probability of an earthquake, other conditions being equal, may vary in certain cases from values around 0.1 to as much as 0.7 or even higher.

Research paper thumbnail of Seismic hazard analysis: How to measure uncertainty?

Computers & Structures, 1998

Applications of probabilistic seismic hazard analysis demand the adoption of a model (i.e. of the... more Applications of probabilistic seismic hazard analysis demand the adoption of a model (i.e. of the forms of a certain number of correlations and probabilistic distributions) and the estimate of the parameters of the model. As a measure of uncertainty in the calculation of the expected value of a given quantity (for instance the peak ground acceleration corresponding to a given return period at a given site) a coecient of variation is frequently adopted, which is intended to include uncertainties due to both the choice of the model and the estimate of parameters. The following three statements are illustrated in this paper: (1) in theory, the use of a coecient of variation, when uncertainties in modeling are involved, is not correct, (2) in practice, the aforesaid use can lead to unreliable results and (3) the analysis of uncertainties can be carried out in a more satisfactory way if uncertainties in modeling and uncertainties in the estimate of parameters are considered separately and with dierent approaches. #

Research paper thumbnail of Statistical Grounds for Favoring the Characteristic Magnitude Model: A Case Study

Bulletin of the Seismological Society of America, 2008

Research paper thumbnail of A proposito di validazione

When a hazard quantity a concerning rare events has to be estimated, the estimated value ais affe... more When a hazard quantity a concerning rare events has to be estimated, the estimated value ais affected by a very large uncertainty. The background hypothesis cannot be validated in an absolute sense: the physical knowledge of rare events is weak; the classic statistical analysis assigns equivalent degree of acceptance to different hypotheses; no direct quantitative evidence can be derived from the poor data set. Here a relative cryterium of validation is used based on an index that measures the variability of estimated quantity; only two competing models are taken in consideration and judged on the basis of the above index.