Sara Luna - Academia.edu (original) (raw)

Papers by Sara Luna

Scandinavian Journal of Statistics, 2003

Kriging is a method for spatial prediction that, given observations of a spatial process, gives t... more Kriging is a method for spatial prediction that, given observations of a spatial process, gives the optimal linear predictor of the process at a new specified point. The kriging predictor may be used to define a prediction interval for the value of interest. The coverage of the prediction interval will, however, equal the nominal desired coverage only if it is constructed using the correct underlying covariance structure of the process. If this is unknown, it must be estimated from the data. We study the effect on the coverage accuracy of the prediction interval of substituting the true covariance parameters by estimators, and the effect of bootstrap calibration of coverage properties of the resulting 'plugin' interval. We demonstrate that plugin and bootstrap calibrated intervals are asymptotically accurate in some generality and that bootstrap calibration appears to have a significant effect in improving the rate of convergence of coverage error.

Earth Surface Processes and Landforms, 2010

Processes controlling sediment yield vary over a range of timescales, although most process-based... more Processes controlling sediment yield vary over a range of timescales, although most process-based observations are extremely short. Lake sediments, however, can be used to extend the observational timescale and are particularly useful when annually laminated (varved) sediment is present. The sediment record at Kassjön (N. Sweden) consists of ∼6400 varves, each 0·5–1 mm thick. Image analysis was used to determine grey-scale variation and varve thickness from which annual minerogenic accumulation rate (MinAR) (mg cm−2 year−1) was inferred for the period 4486 BC – AD 1900. MinAR varies on annual to centennial scales and mainly reflects channel bank erosion by the inflow streams. The mineral input reflects the intensity of the spring run-off, which is dependent on the amount of snow accumulated during the winter, and hence MinAR is a long-term record of variability in past winter climate; other factors will be a variable response to catchment uplift, vegetation succession and pedogenesis. A major shift from low to high MinAR occurred ∼250 BC, and peaks occurred around AD 250, 600, 1000, 1350 and 1650. Wavelet power spectrum analysis (confirmed by Fourier analyses) indicated significantly different periodicities throughout the period 4000 BC – AD 1700, including 275 years for the period 4000 BC – 2900 BC, 567 years for the period 2901 BC – 1201 BC, and 350 and 725 years for the period 1200 BC – AD 1700. The long-term, centennial scale variability (∼350 years) may reflect solar forcing (cf the 385-year peak in tree-ring calibrated 14C activity) but interestingly, there is no obvious link to high frequency forcing, such as the North Atlantic Oscillation. The high resolution component of the record highlights the relevance of varved lake sediment records for understanding erosion dynamics in undisturbed forested catchments and their link to long-term climate dynamics and future climate change. Copyright © 2010 John Wiley & Sons, Ltd.

Journal of Applied Probability, 2000

We introduce the notion of weakly approaching sequences of distributions, which is a generalizati... more We introduce the notion of weakly approaching sequences of distributions, which is a generalization of the well-known concept of weak convergence of distributions. The main difference is that the suggested notion does not demand the existence of a limit distribution. A similar definition for conditional (random) distributions is presented. Several properties of weakly approaching sequences are given. The tightness of

Nowadays new methods of echographic signal processing have emerged to support the medical diagnos... more Nowadays new methods of echographic signal processing have emerged to support the medical diagnosis. In the first stage of development, these methods should be assessed with a considerable number of realistic echo-signals. In this paper, a mathematical model of hepatic tissue is proposed. This will be used to generate echo-graphic signals adjusted to realistic acquired waveforms. The model is based on a set of characteristics computed from echographic signals produced by the inspection of the healthy liver tissue. These characteristics were a) average power, b) signal to noise ratio (SNR) and c) inter-arrival time standard deviation. In order to emulate the realistic signals, the model was fitted accordingly throughout different values of the three parameters. A comparative analysis between real and simulated signals is presented. Conclusions about obtained results are given, including the parameters values (SNR equal to 6 dB, Average Power equal to 4.08e-4 W and an inter-arrival time standard deviation equal to 1.43e-6 s) of the simulated signals that presented the higher correlation coefficient (0.3003).

Nowadays new methods of echographic signal processing have emerged to support the medical diagnos... more Nowadays new methods of echographic signal processing have emerged to support the medical diagnosis. In the first stage of development, these methods should be assessed with a considerable number of realistic echo-signals. In this paper, a mathematical model of hepatic tissue is proposed. This will be used to generate echo-graphic signals adjusted to realistic acquired waveforms. The model is based on a set of characteristics computed from echographic signals produced by the inspection of the healthy liver tissue. These characteristics were a) average power, b) signal to noise ratio (SNR) and c) inter-arrival time standard deviation. In order to emulate the realistic signals, the model was fitted accordingly throughout different values of the three parameters. A comparative analysis between real and simulated signals is presented. Conclusions about obtained results are given, including the parameters values (SNR equal to 6 dB, Average Power equal to 4.08e-4 W and an inter-arrival time standard deviation equal to 1.43e-6 s) of the simulated signals that presented the higher correlation coefficient (0.3003).

Scandinavian Journal of Statistics, 2003

Kriging is a method for spatial prediction that, given observations of a spatial process, gives t... more Kriging is a method for spatial prediction that, given observations of a spatial process, gives the optimal linear predictor of the process at a new specified point. The kriging predictor may be used to define a prediction interval for the value of interest. The coverage of the prediction interval will, however, equal the nominal desired coverage only if it is constructed using the correct underlying covariance structure of the process. If this is unknown, it must be estimated from the data. We study the effect on the coverage accuracy of the prediction interval of substituting the true covariance parameters by estimators, and the effect of bootstrap calibration of coverage properties of the resulting 'plugin' interval. We demonstrate that plugin and bootstrap calibrated intervals are asymptotically accurate in some generality and that bootstrap calibration appears to have a significant effect in improving the rate of convergence of coverage error.

Earth Surface Processes and Landforms, 2010

Processes controlling sediment yield vary over a range of timescales, although most process-based... more Processes controlling sediment yield vary over a range of timescales, although most process-based observations are extremely short. Lake sediments, however, can be used to extend the observational timescale and are particularly useful when annually laminated (varved) sediment is present. The sediment record at Kassjön (N. Sweden) consists of ∼6400 varves, each 0·5–1 mm thick. Image analysis was used to determine grey-scale variation and varve thickness from which annual minerogenic accumulation rate (MinAR) (mg cm−2 year−1) was inferred for the period 4486 BC – AD 1900. MinAR varies on annual to centennial scales and mainly reflects channel bank erosion by the inflow streams. The mineral input reflects the intensity of the spring run-off, which is dependent on the amount of snow accumulated during the winter, and hence MinAR is a long-term record of variability in past winter climate; other factors will be a variable response to catchment uplift, vegetation succession and pedogenesis. A major shift from low to high MinAR occurred ∼250 BC, and peaks occurred around AD 250, 600, 1000, 1350 and 1650. Wavelet power spectrum analysis (confirmed by Fourier analyses) indicated significantly different periodicities throughout the period 4000 BC – AD 1700, including 275 years for the period 4000 BC – 2900 BC, 567 years for the period 2901 BC – 1201 BC, and 350 and 725 years for the period 1200 BC – AD 1700. The long-term, centennial scale variability (∼350 years) may reflect solar forcing (cf the 385-year peak in tree-ring calibrated 14C activity) but interestingly, there is no obvious link to high frequency forcing, such as the North Atlantic Oscillation. The high resolution component of the record highlights the relevance of varved lake sediment records for understanding erosion dynamics in undisturbed forested catchments and their link to long-term climate dynamics and future climate change. Copyright © 2010 John Wiley & Sons, Ltd.

Journal of Applied Probability, 2000

We introduce the notion of weakly approaching sequences of distributions, which is a generalizati... more We introduce the notion of weakly approaching sequences of distributions, which is a generalization of the well-known concept of weak convergence of distributions. The main difference is that the suggested notion does not demand the existence of a limit distribution. A similar definition for conditional (random) distributions is presented. Several properties of weakly approaching sequences are given. The tightness of

Nowadays new methods of echographic signal processing have emerged to support the medical diagnos... more Nowadays new methods of echographic signal processing have emerged to support the medical diagnosis. In the first stage of development, these methods should be assessed with a considerable number of realistic echo-signals. In this paper, a mathematical model of hepatic tissue is proposed. This will be used to generate echo-graphic signals adjusted to realistic acquired waveforms. The model is based on a set of characteristics computed from echographic signals produced by the inspection of the healthy liver tissue. These characteristics were a) average power, b) signal to noise ratio (SNR) and c) inter-arrival time standard deviation. In order to emulate the realistic signals, the model was fitted accordingly throughout different values of the three parameters. A comparative analysis between real and simulated signals is presented. Conclusions about obtained results are given, including the parameters values (SNR equal to 6 dB, Average Power equal to 4.08e-4 W and an inter-arrival time standard deviation equal to 1.43e-6 s) of the simulated signals that presented the higher correlation coefficient (0.3003).

Nowadays new methods of echographic signal processing have emerged to support the medical diagnos... more Nowadays new methods of echographic signal processing have emerged to support the medical diagnosis. In the first stage of development, these methods should be assessed with a considerable number of realistic echo-signals. In this paper, a mathematical model of hepatic tissue is proposed. This will be used to generate echo-graphic signals adjusted to realistic acquired waveforms. The model is based on a set of characteristics computed from echographic signals produced by the inspection of the healthy liver tissue. These characteristics were a) average power, b) signal to noise ratio (SNR) and c) inter-arrival time standard deviation. In order to emulate the realistic signals, the model was fitted accordingly throughout different values of the three parameters. A comparative analysis between real and simulated signals is presented. Conclusions about obtained results are given, including the parameters values (SNR equal to 6 dB, Average Power equal to 4.08e-4 W and an inter-arrival time standard deviation equal to 1.43e-6 s) of the simulated signals that presented the higher correlation coefficient (0.3003).