Indirect Estimation Research Articles

Uncertainty estimation for deep neural networks to improve the assessment of plumage conditions of chickens

The combination of computer vision with deep learning has become a popular tool for automation of labor-intensive monitoring tasks in modern livestock farming. However, uncontrolled and varying environmental conditions, which usually prevail in farmhouses, influence the performance of vision-based applications. Image quality can be reduced, for instance by occlusions, illumination or motions of the animals, which can influence the reliability of those applications. To address this issue, this study proposes an approach for the identification of uncertain neural-network predictions to improve the overall prediction quality. It proposes the direct quantification of aleatoric and epistemic uncertainty on the one hand and indirect estimation of uncertainty through the prediction of occlusions on the other hand. Our approach simultaneously integrates the different methods into an end-to-end trainable instance segmentation and regression model. The objective of this study was to first investigate how well the different measures can quantify the uncertainty of a prediction by comparing them to human uncertainty assessments. Then, it was analyzed whether the uncertainty estimations are capable to identify and reject erroneous predictions by evaluating the correlation between the predictive error and the uncertainty estimations. Finally, individual predictions were rejected based on the estimated uncertainties to analyze the effect on the overall accuracy. As a use-case, the developed methods were applied to the prediction of plumage conditions of chickens but also examined in a separate domain. The results showed that the outputs of our approaches for the estimation of aleatoric and epistemic uncertainty correlate to the predictive error of the model, and lead to increased performance when uncertain predictions are rejected. In contrast, the indirect method to identify occluded samples did not serve as a reliable indicator for uncertainty and could therefore not be used to improve the accuracy of the model outputs.

A pipeline for the fully automated estimation of continuous reference intervals using real-world data

Reference intervals are essential for interpreting laboratory test results. Continuous reference intervals precisely capture physiological age-specific dynamics that occur throughout life, and thus have the potential to improve clinical decision-making. However, established approaches for estimating continuous reference intervals require samples from healthy individuals, and are therefore substantially restricted. Indirect methods operating on routine measurements enable the estimation of one-dimensional reference intervals, however, no automated approach exists that integrates the dependency on a continuous covariate like age. We propose an integrated pipeline for the fully automated estimation of continuous reference intervals expressed as a generalized additive model for location, scale and shape based on discrete model estimates using an indirect method (refineR). The results are free of subjective user-input, enable conversion of test results into z-scores and can be integrated into laboratory information systems. Comparison of our results to established and validated reference intervals from the CALIPER and PEDREF studies and manufacturers’ package inserts shows good agreement of reference limits, indicating that the proposed pipeline generates high-quality results. In conclusion, the developed pipeline enables the generation of high-precision percentile charts and continuous reference intervals. It represents the first parameter-less and fully automated solution for the indirect estimation of continuous reference intervals.

Relationship between Rock Porosity and Infrared Cooling Rate in Non-Standard Specimens of Tuffs Used in the Hungarian Cultural Heritage

This paper is focused on the application of Infrared Thermography to non-standard rock specimens, in terms of size and deterioration conditions, of Hungarian tuff to monitor their cooling process and to look for a relationship between the rock Cooling Rate Index and the porosity. Literature data agree on the potential of Infrared Thermography for the indirect estimation of rock porosity in fresh specimens through the IRTest, but this technique has never been tested on non-standard specimens. To this purpose, tests on three varieties of Hungarian tuffs were carried out. These materials were selected for their cultural importance linked to their usage as building stones and in other historical applications in Northern Hungary. Tuff specimens underwent a fixed number of salt crystallization cycles. The Cooling Rate Index (CRI) for each specimen was calculated according to the literature experience and correlated to their porosity estimated by water, helium, and mercury intrusion. The results show that the rock cooling process is related to porosity since more porous rocks are characterized by faster cooling. Positive linear trends were achieved for weathered specimens considering 20 min monitoring (CRI20), which is double the time suitable for untreated rocks. The reason should be searched in salt crystallization’s effects on the rock texture, paving the way to further studies on this pioneering branch of technological application.

Application of Flow Cytometric Analysis for Measuring Multiple Mitochondrial Parameters in 3D Brain Organoids.

Mitochondrial dysfunction is a common primary or secondary contributor to many types of neurodegeneration, and changes in mitochondrial mass, mitochondrial respiratory chain (MRC) complexes, and mitochondrial DNA (mtDNA) copy number often feature in these processes. Human brain organoids derived from human induced pluripotent stem cells (iPSCs) recapitulate the brain's three-dimensional (3D) cytoarchitectural arrangement and offer the possibility to study disease mechanisms and screen new therapeutics in a complex human system. Here, we report a unique flow cytometry-based approach to measure multiple mitochondrial parameters in iPSC-derived cortical organoids. This report details a protocol for generating cortical brain organoids from iPSCs, single-cell dissociation of generated organoids, fixation, staining, and subsequent flow cytometric analysis to assess multiple mitochondrial parameters. Double staining with antibodies against the MRC complex subunit NADH: Ubiquinone Oxidoreductase Subunit B10 (NDUFB10) or mitochondrial transcription factor A (TFAM) together with voltage-dependent anion-selective channel 1 (VDAC 1) permits assessment of the amount of these proteins per mitochondrion. Since the quantity of TFAM corresponds to the amount of mtDNA, it provides an indirect estimation of the number of mtDNA copies per mitochondrial content. This entire procedure can be completed within a span of 2-3 h. Crucially, it allows for the concurrent quantification of multiple mitochondrial parameters, including both total and specific levels relative to the mitochondrial mass.

Characterization and Liberation Study of the Beauvoir Granite for Lithium Mica Recovery

A significant proportion of Europe’s lithium endowment is hosted by unconventional lithium resources such as rare-metal granites (RMG) of which the Beauvoir granite in France is a prime example. In such hard-rock deposits, where lithium is mostly hosted in micas (lepidolite, zinnwaldite), the ability to assess whether lithium can be extracted economically from the ore is essential and requires a comprehensive understanding of mineralogical properties and lithium deportment. Using three exploratory drill cores distributed along the North–South axis, a preliminary geometallurgical assessment of the granite has been conducted based on a combination of techniques including Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES), Atomic Adsorption Spectroscopy (AAS), Electron Probe Microanalysis (EPMA), Scanning Electron Microscope (SEM) coupled with automated mineralogy software, X-Ray Diffraction (XRD), optical microscope and sieving. Lithium distribution appears to be variable, reflecting the evolution of the granite, with higher mica content in the southern area and higher Li grade towards the center of the orebody. The size of micas in the assessed sample does not vary significantly. The grindability and liberation size of micas varies in the different zones investigated, PERC S being the most difficult to grind. There is always more than 50 wt% of the micas that are liberated in the samples when crushed to 1 mm. Indirect estimation of Li content based on EPMA and SEM analysis suggests that the content of lithium inside mica crystals could vary. If this estimation is confirmed by direct Li measurement, it for sure makes the calculations of the Li deportment more challenging.

Indirect measurement of propeller fluctuating forces using an inverse analysis: Numerical and experimental studies

The propeller fluctuating force is being recognized as the dominant source of underwater radiated noise, its accurate acquisition is thus necessitated for a reliable acoustic-structure analysis and optimization of marine ships. However, such dynamic operational forces are frequently impossible or expensive to directly measure due to various practical challenges. To alleviate this limitation, this paper presents an inverse method for the indirect estimation of propeller forces using measured shafting vibration responses. The force reconstruction procedure is constructed based on the state-space model of the propeller–shafting system, which can be derived by a data-driven subspace identification algorithm in conjunction with either the numerical or experimental models of the system. To ensure the robustness of the inverse analysis in the presence of inevitable measurement noise, a modified regularization strategy based on homotopy continuation is introduced. The effectiveness of the proposed algorithm is demonstrated through numerical simulations and experimental investigations. The obtained results demonstrate the potential feasibility of indirect measurement for accurately identifying propeller fluctuating forces in the time domain.

Socio-economic differentials of under-five mortality in Botswana: an application of the indirect estimation method

Abstract Background Socio-economic differentials in infant and under-five mortality exist in all countries worldwide, but the extent of differentials varies across countries. This study aimed to examine the socio-economic differentials of under-five mortality in Botswana within the framework of equality and equity. Methods and findings The analysis for this paper was based on the data from 2001 and 2011 Botswana Population and Housing Censuses and the 2017 Botswana Demographic Survey. One census method was used to indirectly estimate under-five mortality for different socio-economic groups using Princeton west model life tables. Results from this study revealed that socio-economic disparities in under-five mortality disfavouring the worse-off exist in all the selected socio-economic variables. The variations of socio-economic groups by mother’s place of residence and employment status have been narrowing over time, whereas the differences of socio-economic groups by mother’s level of education and marital status have been widening over time. Conclusions The findings of this study show that policies and interventions targeted at reducing inequalities should reach all socioeconomic groups across the country. Differences of each society and localities should be considered while designing and implementing policies and interventions.

Evaluation of the influence of correcting for gillnet selectivity on the estimation of population parameters.

Gill nets are a common sampling technique in inland and marine fisheries. However, gill nets are size selective and may result in bias estimates of population parameters. As such, selectivity is commonly assessed using indirect estimation techniques. Indirect estimates of gillnet selectivity have been suggested to improve estimates of important populations metrics (e.g., total annual mortality), but this assertion has not been assessed. In the current study, we simulated hypothetical populations of channel catfish Ictalurus punctatus, lake trout Salvelinus namaycush, walleye Sander vitreus, and white crappie Pomoxis annularis and sampled the populations based on published gillnet encounter and retention probabilities. Total annual mortality and von Bertalanffy parameters were then estimated using unadjusted (not "correcting" for selectivity processes) and adjusted ("correcting" for selectivity processes) age and(or) length data to evaluate the value of accounting for gillnet selectivity when estimating these metrics. Our results indicate that adjusting for retention and encounter probabilities rarely leads to improved estimates of total annual mortality, K, and L∞. For instance, estimates of annual mortality of lake trout based on age data adjusted for retention probability resulted in an overestimate of A by 14.4%. As such, we suggest that analysis of gillnet selectivity only be used when specific questions are being addressed (e.g., catch-at-age models) or in situation when all processes contributing to gillnet selectivity (e.g., contact probability, size-specific availability) are known.

A novel approach to CSF pressure measurement via lumbar puncture that shortens the measurement time with a high level of accuracy

Intracranial pressure (ICP) is an important parameter in clinical management and diagnosis of several neurological diseases which is indirectly measured via lumbar puncture (LP). In routine measurements of cerebrospinal fluid pressure (PCSF) from lumbar region, a spinal needle and a spinal manometer are used. PCSF measurement via LP with the use of a spinal manometer may not yield correct PCSF results due to prolonged times required to obtain an accurate pressure value. Equilibrium pressure may be underestimated in circumstances where spinal manometry procedure is terminated prematurely, with the wrong assumption that equilibrium pressure is reached. Elevated PCSF levels can lead to visual loss and brain damage when go undiagnosed. In this study, the spinal needle-spinal manometer combination was modelled with a first-order differential equation and a time constant (τ) was defined as the product of the resistance to flow of the needle with the bore area of the manometer divided by the dynamic viscosity of CSF, i.e. τ= RA/ρCSF. Each needle/manometer combination had a unique constant as a predictor of the equilibrium pressure. The fluid pressure in the manometer rose in an exponential manner which was tested in a simulated environment using 22G spinal needles namely Braun-Spinocan, Pajunk-Sprotte and M.Schilling. Curve fitting of the manometer readings were obtained with regression coefficients of R2 ≥ 0.99 to determine measurement time constants. The residual differences between predicted and true values were less than 1.18 cmH2O. For a given needle/manometer combination, time required to reach equilibrium pressure was identical for all pressure levels. PCSF measured at reduced times can easily be interpolated to their equilibrium level allowing clinicians to obtain PCSF values with high accuracy within seconds. This method can be used as an indirect estimation of ICP in routine clinical practice.

Direct and indirect ground estimation of leaf area index to support interpretation of NDVI data from satellite images in hedgerow olive orchards

In discontinuous crop soil coverage condition, as for many horticultural crops (e.g. fruit or olive orchard), the low spatial resolution of freely available reflectance data acquired from satellites, affects their agronomic use. Each reflectance pixel value is influenced not only by the reflectance response of the target crop but also by the percentage of pixel covered by the crop, as bare soil and/or spontaneous vegetation strongly affects whole pixel reflectance.In this context, when the analysis of crop conditions is the main agronomical target, the measurement of Leaf Area Index (LAI), supporting the estimation of the area covered by the discontinuous crop, could represent a crucial step helping the interpretation of remote sensed spectral data including related vegetation indices.From this perspective, a field experiment has been conducted on an 8.30 ha super intensive hedgerow olive orchard, monitoring (i) variation of NDVI from an 830 pixels’ grid of the Sentinel-2 imagery (10×10 m) during two years (2020–2021); (ii) LAI estimated by destructive measurement, and (iii) LAI estimated by light transmittance at soil level under the crop measured by a commercial low cost field instrument (LAI-Pen LP 100) with two light sensors (400 - 700 nm and 400 - 500 nm bands).Mean NDVI elaborated from Sentinel-2 imagery and referred to the whole orchard, varies from 0.28 to 0.81, along the two years, and was quite stable during the summer months for each year (0.28–0.36 in 2020 and 0.39–0.41 in 2021). LAI estimated by destructive measurements on single plants, ranged between 2.17 and 4.38. LAI estimated by LAI-Pen, was strongly related to LAI estimated by destructive measurements (R2=0.9473 n = 9)Finally, the average of LAI-Pen measurements referred to all the plants (n = 16) included in each pixel of the Sentinel 2 measurements’ grid, resulted directly correlated to pixel NDVI values collected in the same date.

Prevalence of opioid dependence in New South Wales, Australia, 2014-16: Indirect estimation from multiple data sources using a Bayesian approach.

To estimate the prevalence of, and number of unobserved people with opioid dependence by sex and age group in New South Wales (NSW), Australia. We applied a Bayesian statistical modelling approach to opioid agonist treatment records linked to adverse event rate data. We estimated prevalence from three types of adverse event separately: opioid mortality, opioid-poisoning hospitalizations and opioid-related charges. We extended the model and produced prevalence estimates from a 'multi-source' model based on all three types of adverse event data. This study was conducted in NSW, Australia, 2014-16 using data from the Opioid Agonist Treatment and Safety (OATS) study, which included all people who had received treatment for opioid dependence in NSW. Aggregate data were obtained on numbers of adverse events in NSW. Rates of each adverse event type within the OATS cohort were modelled. Population data were provided by State and Commonwealth agencies. Prevalence of opioid dependence among those aged 15-64 years in 2016 was estimated to be 0.96% (95% credible interval [CrI] = 0.82%, 1.12%) from the mortality model, 0.75% (95% CrI = 0.70%, 0.83%) from hospitalizations, 0.95% (95% CrI = 0.90%, 0.99%) from charges and 0.92% (95% CrI = 0.88%, 0.96%) from the multi-source model. Of the estimated 46 460 (95% CrI = 44 680, 48 410) people with opioid dependence in 2016 from the multi-source model, approximately one-third (16 750, 95% CrI = 14 960, 18 690) had no record of opioid agonist treatment within the last 4years. From the multi-source model, prevalence in 2016 was estimated to be 1.24% (95% CrI = 1.18%, 1.31%) in men aged 15-44, 1.22% (95% CrI = 1.14%, 1.31%) in men 45-64, 0.63% (95% CrI = 0.59%, 0.68%) in women aged 15-44 and 0.56% (95% CrI = 0.50%, 0.63%) in women aged 45-64. A Bayesian statistical approach to estimate prevalence from multiple adverse event types simultaneously calculates that the estimated prevalence of opioid dependence in NSW, Australia in 2016 was 0.92%, higher than previous estimates.

Incidence of keratinocyte carcinomas in Italy: an exercise in indirect estimation based on melanoma data.

The occurrence of keratinocyte carcinomas (KC) worldwide appears to be increasing, however, information on the actual incidence of these tumours is often incomplete. The aim of this study was to provide information on the KC/melanoma ratio in order to indirectly estimate the occurrence of KC. Data were collected according to a snowball sampling procedure between Italian dermatologists. Colleagues working on melanoma and non-melanoma units were excluded. These ratios were applied to estimates derived from histopathological records, namely melanoma incidence estimates available from the Italian National Cancer Registry Network. The final estimates for KC incidence were thus obtained using the formula: KC incidence (per 100,000) = melanoma incidence (per 100,000) * (KC/melanoma ratio). Our results revealed a BCC/melanoma ratio of 4.4 and SCC/melanoma ratio of 1.7; values that are approximately 4 to 5 times smaller than those self-reported by dermatologists. Interestingly, this large discrepancy was not observed for the BCC/SCC ratio, which was 2.5 in the north, 2.7 in the centre, and 3.2 in the south of Italy, with an overall value of 2.8. Based on the histopathological data, this ratio was 2.6. In Italy, the actual occurrence of BCC and SCC seems to be vastly underestimated based on histopathological data, compared to data reported by dermatologists.

Comparison of three indirect methods for verification and validation of reference intervals at eight medical laboratories: a European multicenter study

Abstract Objectives Indirect methods for the indirect estimation of reference intervals are increasingly being used, especially for validation of reference intervals, as they can be applied to routine patient data. In this study, we compare three statistically different indirect methods for the verification and validation of reference intervals in eight laboratories distributed throughout Europe. Methods The RefLim method is a fast and simple approach which calculates the reference intervals by extrapolating the theoretical 95 % of non-pathological values from the central linear part of a quantile-quantile plot. The Truncated Maximum Likelihood (TML) method estimates a smoothed kernel density function for the distribution of the mixed data, for which it is assumed that the ‘‘central’’ part of the distribution represents the healthy population. The refineR utilizes an inverse modelling approach. This algorithm identifies a model that best explains the observed data before transforming the data with the Box-Cox transformation. Results We show that the different indirect methods each have their advantages but can also lead to inaccurate or ambiguous results depending on the approximation of the mathematical model to real-world data. A combination of different methodologies can improve the informative value and thus the reliability of results. Conclusions Based on routine measurements of four enzymes alkaline phosphatase (ALP), total amylase (AMY), cholinesterase (CHE) and gamma-glutamyl transferase (GGT) in adult women and men, we demonstrate that some reference limits taken from the literature need to be adapted to the laboratory’s particular local and population characteristics.

Effect of Characteristic Impedance in Estimating Specific Energy and Average Fragment Size at High Strain Rates of Some Peridotitic Rock Materials at Laboratory Scale

In this study, the application of characteristic impedance in estimating specific energy and average fragment size of rocks was investigated during rock breakage at high strain rates. To achieve this, rock specimen was prepared in accordance with recommendations of the International Society for Rock Mechanics and broken at high strain rates using the split Hopkinson’s pressure bar system. Results reveal that although strain rate is well related to specific energy and average fragment size of broken rocks, the product of characteristic impedance and strain rate is more reliable for estimating the forementioned parameters. In addition, strain rate and dissipated energy generally increase at higher incident energies while the average fragment size of broken rocks reduces at higher strain rates. Based on these findings, more studies on indirect estimation of energy requirement for rock breakage to desired average fragment sizes is recommended from the product of characteristic impedance and strain rate.

P391 THE DIAGNOSTIC CHALLENGE BETWEEN CHRONIC PULMONARY EMBOLISM AND PULMONARY ARTERY SARCOMA: A CASE REPORT

Abstract We report the case of a 63–year–old obese and hypertensive woman, admitted in hospital with worsening dyspnea for 2 weeks and syncope. A suspected chronic thromboembolism was diagnosed nine months before for a similar clinical picture; hematologic screening excluded thrombophilia and NOACs were prescribed. Two–dimensional transthoracic echocardiography showed enlargement of right chambers, the interventricular septum shifted to the left ventricle, showing “D” sign. Color Doppler flow imaging showed moderate regurgitation in tricuspid valve, with indirect pulmonary pressure estimation 90 mmHg. Left ventricle was normal for dimensions and function. ECG evidenced sinus tachycardia and no specific ST–T alterations. Blood exams evidenced anemia (Hb 9 mg/dl), negative neoplastic markers and absence of occult blood in feces, mildly elevated inflammatory markers, T–Troponin and D–dimer. Naso–pharyngeal swab for SARSCoV2 infection was negative. Chest computed tomography with contrast revealed a large filling defect within bilateral main pulmonary arteries. No lymph nodes or pulmonary pneumonia were detected. Lower extremity venous ultrasound was positive for right popliteal deep vein thrombosis. The global clinical picture suggested an acute pulmonary embolism recurrence, with a severe right ventricle impairment and a concomitant deep vein thrombosis. Some factors were not completely clear: chronic anemia, only mildly increased D–dimer, no specific increase of inflammatory markers. The patient was referred to Cardiac Surgery Unit of IRCCS Foundation Policlinico San Matteo in Pavia, for pulmonary endarterectomy. Unexpectedly the surgical finding was a bilateral pulmonary artery sarcoma, confirmed by histological exam. We thus clarified some uncertain clinical aspects, explainable in the context of a severe neoplastic picture. There were no immediate complications, and a chemotherapy was initiated after a period of cardio–pulmonary rehabilitation. Pulmonary artery intimal sarcoma is a very rare disease, its prevalence is about 0.001–0.003%, it can originate from the left and right pulmonary arteries and intimal layer of pulmonary arteries, forming a tumor growing in the nodular cavity or spreading along the intimal surface. PAS is often misdiagnosed as acute or chronic pulmonary thromboembolism due to its clinical presentation and radiological findings. Thus, early diagnosis is very crucial and may improve patient outcome.

Indirect force estimation method under spectrally varying and amplitude-sensitive conditions by estimating the effective fluid path parameter

Indirect methods to estimate the force transmitted from the source to the receiver have been investigated using various approaches to increase accuracy and overcome discrepancies, especially when the measurements are conducted in situ. To implement the indirect force estimation techniques in situ, developing an accurate measurement method and establishing reasonable system models always matter when the force estimations involve nonlinear internal forces such as the upper chamber pressures of the hydraulic mount system. Based on prior research conducted on force estimation in a nonlinear hydraulic mount, a simplified reverse-path spectral method is proposed in this study for estimating the force transmitted from the driving point to the ground by focusing on one effective fluid path parameter. To achieve the purpose of this study, two interfacial force datasets from the non-resonant test were first captured along with spectrally varying and amplitude-sensitive conditions. Second, two different path forces were determined from the rubber and hydraulic paths, and the effective fluid path parameter (EFP) was estimated from the hydraulic path force. The employment of the EFP contributes to estimating the effective internal properties, which show better correlations with the measurements than the estimated results from prior studies. Thus, the current work, performed by focusing on the EFP, successfully suggests a simplified yet efficient way to develop an indirect force estimation method in a nonlinear hydraulic mount as a dynamic load sensing system.

Prediction of Post-stroke Motor Recovery Benefits from Measures of Sub-acute Widespread Network Damages (P12-8.002)

<h3>Objective:</h3> Developing a more accurate post-stroke motor recovery prediction model leveraging brain network connectivity measurements. <h3>Background:</h3> Following an acute ischemic stroke, some patients recover almost completely, while others barely recover. It is known that lesion volume, initial motor impairment, and cortico-spinal tract asymmetry (benchmark features) significantly impact motor changes over time. However, accurate prediction models of patients’ recovery are still missing. Recent work suggested that disabilities arise not only from focal structural changes but also from widespread alterations in inter-regional connectivity. Here, we built on this hypothesis to develop a more accurate post-stroke motor recovery prediction model. <h3>Design/Methods:</h3> We evaluated a dataset of 37 patients (17 women) with upper extremity motor strokes. Their impairment was assessed at 2 weeks (baseline) and 3 months after the stroke using the Fugl-Meyer-Assessment. 18 graph measures of global structural connectivity were obtained using the patients’ T2 lesion mask to virtually reproduce the lesions in 60 healthy streamline tractography connectomes. We added these indirect measures to the benchmark features, and we used a ridge regression regularization in a leave-one-out cross-validation framework to predict motor recovery at 3 months post-injury. <h3>Results:</h3> Prediction accuracy significantly increased when using brain connectivity measures (R²=0.68, 95% CI: 0.64–0.74) as compared to benchmark features alone (R²=0.38, 95% CI: 0.31–0.51). <h3>Conclusions:</h3> We report that global measures of brain connectivity estimated by introducing virtual lesions in healthy structural connectomes significantly increase the accuracy of motor recovery prediction in stroke patients compared to focal and clinical measures used until now. This indirect estimation of the stroke impact on the whole brain connectome is more readily available than direct measures of structural connectivity obtained with magnetic resonance imaging (MRI) and would, therefore, have a more substantial clinical impact. <b>Disclosure:</b> An immediate family member of Dr. Pirondini has stock in Reach Neuro. The institution of Dr. Pirondini has received research support from NIH. The institution of an immediate family member of Dr. Pirondini has received research support from NIH. Dr. Pirondini has received intellectual property interests from a discovery or technology relating to health care. An immediate family member of Dr. Pirondini has received intellectual property interests from a discovery or technology relating to health care. Maria Giulia Preti has nothing to disclose. Dimitri Van De Ville has nothing to disclose. Prof. Guggisberg has nothing to disclose. Dr. Rivier has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Pyxis Partners.

Estimating daily precipitation climatology by postprocessing high‐resolution reanalysis data

AbstractSpatial information of climatological frequency distribution of daily precipitation is highly valuable for a wide range of applications. Accurate estimation of climatology can be made for gauged locations where quality and lengthy observations are available. For ungauged or poorly gauged locations, however, indirect estimation is needed. One approach is to use a gridded daily precipitation dataset derived from interpolating observations. However, gridded daily precipitation data can be subject to large errors when gauge density is low. In addition, most interpolation methods tend to smooth the extreme values and increase the low ones, leading to unrealistic statistical properties and therefore poor estimation of daily climatology. Another approach is to first derive climatology at gauged locations and then interpolate climatology to ungauged locations. While this approach is likely to be more robust than the first approach, low gauge density can still cause significant errors especially in areas of complex terrain. In this study, we develop a method that postprocesses spatially consistent and rich reanalysis data using accurate observations at gauged locations. At an ungauged location, daily precipitation amounts from the reanalysis are bias‐corrected using quantile‐mapping guided by frequency distributions of reanalysis data and observations at a nearby gauged location (reference location). The bias‐corrected precipitation amounts are then used to estimate the climatology for the ungauged location. This method eliminates the need for interpolation and therefore its adverse effects. Special care is taken in quantile‐mapping when extrapolating beyond the range of reanalysis data at the reference location. We evaluate the method at 50 locations in Australia, using the Bureau of Meteorology Atmospheric high‐resolution Regional Reanalysis for Australia (BARRA) and precipitation observation network across Australia. These locations are chosen to represent different climate regions in Australia and have observations to validate the postprocessed reanalysis climatology of daily precipitation. Results show that the postprocessed climatology is consistent with observations, in terms of frequency distribution, high quantiles, probabilities of wet and dry days and their transitions.

Indirect inference estimation of stochastic production frontier models with skew-normal noise

Indirect inference estimation of stochastic production frontier models with skew-normal noise

Indirect Estimation of the Timing of First Union Dissolution With Incomplete Marriage Histories

The lack of nationally representative data with detailed marriage histories in low- and middle-income countries (LMICs) impedes a comprehensive understanding of essential aspects of union dissolution, such as the timing of first union dissolution, in these countries. We propose a method for estimating quantum-adjusted measures of the timing of first union dissolution from incomplete marriage histories. This method, indirect life table of first union dissolution (ILTUD), estimates the first union survival function from a simple tabulation of ever-married women by duration since first union, classified by union dissolution status (intact vs. dissolved first union). It then uses the relationships between life table functions to generate the distribution of marriages ending each year (θt) for a given marriage cohort. Using this distribution, ILTUD generates quantum-adjusted first union survival rates from which the percentiles of first union dissolution are calculated. ILTUD estimates are consistent with estimates produced using traditional statistical methods, such as the Kaplan–Meier estimator. In addition, ILTUD is simple to implement and has minimal data requirements, which are available in most nationally representative surveys. Thus, the ILTUD method has the potential to broaden our understanding of union dissolution dynamics in LMICs.