Graphical Analysis Method Research Articles

Региональные особенности соблюдения требований FATF

Increasingly expanding international requirements in the field of combating money laundering and terrorist financing(AML/CFT) force the public and financial sector to seek a balance between the rising costs of their implementation andsanctions threats for non-compliance. A number of scientific publications describe regional AML/CFT cooperation in theEuropean Union (EU) as an example of such a balance. Some EU countries coordinate their actions within the frameworkof the Financial Action Tasks Force on Money Laundering (FATF), which is the methodological centre of the global antimoneylaundering movement. Russia is a member of the FATF and its two regional groups: Moneyval, organized by theCouncil of Europe, and the Eurasian Group (EAG) initiated by Russia itself, which unites Russiaʼs neighbouring, mainlyAsian, countries. This study covers the results of assessments of compliance by EU and EAG countries with FATF requirementsin order to study approaches to AML/CFT regional cooperation and to identify problems arising in this process andprospects for international cooperation. The methods of comparative and graphical analysis were used. The authors showthat deep regional integration of lawmaking is not in itself a fundamental factor in achieving equally high rates of compliancewith FATF requirements. Indifference to matters of monitoring compliance with approved regional anti-money launderingstandards allows particular EU countries to act in the national interest, contrary to the 40 FATF recommendations and thegoals of the global AML/CFT regime. On the contrary, the EAG countries demonstrate steady progress in the introductionof legislation and practical implementation of FATF requirements, which indicates their collective awareness of the benefitsfrom financial information transparency and the possibility of exchanging this information at the international level.

Fintech tools for predicting bankruptcy: integration of traditional and innovative approaches

Methods. The theoretical and methodological basis of the study is the scientific developments of domestic and foreign scholars related to the issues of determining the role and features of using traditional discriminant models of bankruptcy forecasting and modern FinTech tools. The results of the study were obtained using the methods of abstraction; general and particular – in establishing the unity of existing traditional methods of bankruptcy forecasting and innovative FinTech technologies; the systematic method was used to systematise a wide range of FinTech tools specifically designed to predict the bankruptcy of enterprises, the method of generalisation – in identifying common digital elements to create analytical capabilities for managing the financial activities of an enterprise and risk management. Methods of theoretical and empirical research, including abstraction and comparison, were also used to identify the specifics of applying various forecasting models and the capabilities and advantages of FinTech tools. Graphical analysis methods were used to visualise the results of the study. Results. The results of the study revealed the potential of integrating discriminant models and FinTech tools in bankruptcy forecasting, which will help improve financial analysis and risk management in the context of economic changes. The article shows that the use of discriminant models for predicting bankruptcy has the potential to improve financial analysis and effective risk management. These models allow to take into account various financial indicators and factors that affect the probability of bankruptcy of an enterprise. They provide an opportunity to assess a company's financial stability and ability to repay its liabilities. If used correctly, these models can help to ensure early detection of financial problems and take effective measures to prevent bankruptcy. Novelty. In the course of the study of bankruptcy forecasting models, it is established that the optimal combination of discriminant models and FinTech tools provides an opportunity to obtain accurate forecasts of the further functioning and development of enterprises and opens up new prospects for financial analysis to avoid risks and implement effective innovative solutions in today's changing environment. Practical value. It is the ability to integrate traditional and innovative approaches to solving specific problems related to bankruptcy forecasting and the development of enterprises in an unstable environment.

Nonlinear Modeling and Improved Suppression of Zero-Sequence Circulating Current for Parallel Three-Level Inverters

The parallel operation of three-level inverters can increase the current capacity and power rating of the system. However, the problem of zero-sequence circulating current (ZSCC) inevitably emerges due to the common-mode voltage difference (CMVD) between the parallel three-level inverters (PTLIs). Especially, the inverter nonlinear characteristics (INCs) will worsen the ZSCC problem and weaken the suppression effect of ZSCC. In this paper, a nonlinear equivalent model of ZSCC is established considering the INCs. Then, the simplified graphical analysis method is proposed to implement the frequency analysis of ZSCC. Furthermore, an improved ZSCC suppression strategy for the PTLIs is proposed. The INCs and original CMVD are regarded as the total disturbance and a nonlinear disturbance observer (NDOB) is designed to estimate it. Based on the NDOB, a feedback-feedforward control method is adopted to suppress ZSCC. According to the amplitude-frequency characteristics of the closed-loop control system, the controller parameters design and performance analysis are performed. The control structure is simple, the parameter design is convenient, and the suppression effect of ZSCC is evidently improved. Finally, the simulation and experimental results verify the validity of proposed strategy.

Acceleration of the EM algorithm

AbstractThe expectation–maximization (EM) algorithm is a well‐known iterative algorithm for finding maximum likelihood estimates from incomplete data and is used in several statistical models with latent variables and missing data. The algorithm also exhibits a monotonic increase in a likelihood function and satisfies parameter constraints for its convergence. The popularity of the EM algorithm can be attributed to its stable convergence, simple implementation and flexibility in interpreting data incompleteness. Despite these computational advantages, the algorithm is linear convergent and suffers from very slow convergence when a statistical model has many parameters and a high proportion of missing data. Various algorithms have been proposed to accelerate the convergence of the EM algorithm. We introduce the acceleration of the EM algorithm using root‐finding and vector extrapolation algorithms. The root‐finding algorithms include Aitken's method and the Newton–Raphson, quasi‐Newton and conjugate gradient algorithms. These algorithms with faster convergence rates allow the EM algorithm to be sped up. The vector extrapolation algorithms transform the sequence of estimates from the EM algorithm into a fast convergent sequence and can accelerate the convergence without modifying the EM algorithm. We describe the derivation of these acceleration algorithms and attempt to apply them to two examples.This article is categorized under: Statistical and Graphical Methods of Data Analysis > EM Algorithm

On calibrated inverse probability weighting and generalized boosting propensity score models for mean estimation with incomplete survey data

AbstractIncomplete data, whether realized from nonresponse in survey data or counterfactual outcomes in observational studies, may lead to biased estimation of study variables. Nonresponse and selection bias may be mitigated with techniques that weight the incomplete data to match characteristics of the partially unobserved complete data. Inverse probability weighting is a widely used method in causal inference that relies on a propensity model to construct adjusted weights; whereas calibration is a common method used by survey statisticians to use constrained optimization to construct adjusted weights. This article reviews inverse probability weighting and entropy balancing calibration by distinguishing them in the statistical sense of variable balancing, extending propensity score construction to include generalized boosting models, and demonstrating the use of inverse probability weighting and calibration separately and together through a widely cited simulation study evaluation.This article is categorized under: Statistical and Graphical Methods of Data Analysis > Sampling Data: Types and Structure > Categorical Data Statistical Learning and Exploratory Methods of the Data Sciences > Modeling Methods

Trend analysis of precipitation using innovative approaches in northwestern Turkey

Precipitation is highly sensitive to climate change, and monitoring its trends over time is essential for understanding the effects of global warming on the Earth's water cycle. This study investigates the effects of climate change on monthly precipitation in the Susurluk Basin located in northwestern Turkey, using innovative trend analysis methods. Innovative Polygon Trend Analysis (IPTA) using star graphics and Improved Visualization for Innovative Trend Analysis (IV-ITA) techniques were used to analyze precipitation data from nine stations in the basin over 50 years (1970–2019), and the findings were compared to classical Mann-Kendall (MK) results. According to the trend analysis results, the MK method detected significant trends in only two months in the decreasing direction. In these decreasing trends observed at Simav and Keles stations in November, z values were calculated as −2.38 and −2.05, respectively. IPTA method detected increasing trends in 54 months and decreasing trends in 40 months; this means there is a change of more than 5% between two half series. The IV-ITA method indicated an increase of more than 40% in the low values for January, March, August, and September. In addition, there was an increasing trend of more than 40% in the high values observed in September at all stations. It was observed that mean precipitation heights increased from September to December and then decreased throughout the basin. It is predicted that decreases in precipitation during dry seasons may put intense pressure on agricultural water use and affect water quality. In addition, the increase in precipitation in spring months may increase flood events. It was determined that graphical innovative trend analysis methods are more effective in trend identification than MK, and these methods' results have much higher visual inspection and linguistic interpretation possibilities. Innovative methods allow for more flexible and in-depth analysis using different statistical parameters.

Neuroimaging statistical approaches for determining neural correlates of Alzheimer's disease via positron emission tomography imaging

AbstractAlzheimer's disease (AD) is a degenerative disorder involving significant memory loss and other cognitive deficits, manifesting as a progression from normal cognitive functioning to mild cognitive impairment to AD. The sooner an accurate diagnosis of probable AD is made, the easier it is to manage symptoms and plan for future therapy. Functional neuroimaging stands to be a useful tool in achieving early diagnosis. Among the many neuroimaging modalities, positron emission tomography (PET) provides direct regional assessment of, among others, brain metabolism, cerebral blood flow, amyloid deposition—all quantities of interest in the characterization of AD. However, there are analytic challenges in identifying early indicators of AD from these high‐dimensional imaging data sets, and it is unclear whether early indicators of AD are more likely to emerge in localized patterns of brain activity or in patterns of correlation between distinct brain regions. Early PET‐based analyses of AD focused on alterations in metabolic activity at the voxel‐level or in anatomically defined regions of interest. Other approaches, including seed‐voxel and multivariate techniques, seek to characterize metabolic connectivity by identifying other regions in the brain with similar patterns of activity across subjects. We briefly review various neuroimaging statistical approaches applied to determine changes in metabolic activity or metabolic connectivity associated with AD. We then present an approach that provides a unified statistical framework for addressing both metabolic activity and connectivity. Specifically, we apply a Bayesian spatial hierarchical framework to longitudinal metabolic PET scans from the Alzheimer's Disease Neuroimaging Initiative.This article is categorized under: Statistical and Graphical Methods of Data Analysis > Analysis of High Dimensional Data Statistical Learning and Exploratory Methods of the Data Sciences > Modeling Methods Statistical Models > Bayesian Models

Competitive skill of Paspalum virgatum L.e o Panicum maximum cv. Mombaça in different soil fertilities

This work aimed to study the competitive ability between Paspalum virgatum L. and Panicum maximum cv. Mombaça in different soil fertilities. Three independent experiments were set up in a completely randomized design, with four replications. Each experiment corresponded to different levels of soil fertility (low, medium and high) and were arranged in a substitutive series in the proportions of 100:0, 75:25, 50:50, 25:75 and 0:100% of Panicum maximum cv. Mombaça with Paspalum virgatum L. The height, number of tillers and the dry matter mass of the plants were determined 60 days after the emergence of the species. Data were analyzed using the graphical analysis method, constructing diagrams based on productivity or relative and total variations, determining the competitiveness indices (CR), grouping coefficient (K) and relative aggressiveness (A). For the three fertility levels of the soils studied, the crop was superior to the competitor in terms of height, tillering and dry matter accumulation in the proportions of equivalent population densities (50:50), proving greater competitive ability through relative competitiveness values greater than 1 and crop aggressiveness greater than 0.

ANALYSIS OF MODERN PRACTICE IN IMPLEMENTING PUBLIC-PRIVATE PARTNERSHIP PROJECTS

Attracting private investment to solve social and economic problems is an important task for any state. Implementation of infrastructure projects, coupled with social and economic programs, allows the state to pursue a compact, efficient and flexible policy. The mechanism of partnership relations between the state and private business that has developed in world practice in the implementation of socially significant investment projects represents a new stage in state regulation of the economy. The use of the investment mechanism in Russian conditions is possible, especially in those areas of activity where private investment is able to ensure sustainable economic growth, while maintaining the control functions of the state. Today, the economic situation of the subjects of the Russian Federation requires the use of new tools to assess their economic potential, socio-economic development and competitiveness. Such tools are important for an active federal policy aimed at leveling interregional inequality and ensuring the economic integrity of the country. The purpose of the work is to explore the world experience in the implementation of public-private partnership projects as a promising form of interaction between the state and business. The methods of scientific research are synthesis, statistical and comparative analysis, methods of systemic and graphical analysis. The subject of the study is a system of relations between the state and business, focused on the creation and operation of social and industrial infrastructure facilities. Based on the analysis, it was noted that public-private partnership is a more popular and attractive form of relationship between the state and business in modern conditions and abroad.

Sampling constrained continuous probability distributions: A review

AbstractThe problem of sampling constrained continuous distributions has frequently appeared in many machine/statistical learning models. Many Markov Chain Monte Carlo (MCMC) sampling methods have been adapted to handle different types of constraints on random variables. Among these methods, Hamilton Monte Carlo (HMC) and the related approaches have shown significant advantages in terms of computational efficiency compared with other counterparts. In this article, we first review HMC and some extended sampling methods, and then we concretely explain three constrained HMC‐based sampling methods, reflection, reformulation, and spherical HMC. For illustration, we apply these methods to solve three well‐known constrained sampling problems, truncated multivariate normal distributions, Bayesian regularized regression, and nonparametric density estimation. In this review, we also connect constrained sampling with another similar problem in the statistical design of experiments with constrained design space.This article is categorized under: Applications of Computational Statistics > Computational Mathematics Statistical and Graphical Methods of Data Analysis > Bayesian Methods and Theory Statistical and Graphical Methods of Data Analysis > Markov Chain Monte Carlo (MCMC) Statistical and Graphical Methods of Data Analysis > Sampling

IOS “Voice Memo” Audio Files Originality Authentication

In this paper, we modify the audio files recorded by IOS “Voice Memo” by cutting and erasing them in the software, and use various software and websites to authenticate the audio files originality by taking the method of graphical analysis and metadata feature analysis of the files. By comparison, we find out the differences of the original and modified audio files and the general method of judging the originality of audio files. The results of the experiments show that the audio files generated by the IOS system's own voice memo are in M4A format by default and that the audio files generated in the IOS system environment have the important feature of system version information encoding.

Global Value Chains and Industry 4.0 in the Context of Lean Workplaces for Enhancing Company Performance and Its Comprehension via the Digital Readiness and Expertise of Workforce in the V4 Nations

Industry 4.0 affects nearly every aspect of life by making it more technologically advanced, creative, environmentally friendly and ultimately, more interconnected. It also represents the beginning of the interconnectedness and metaverse associated with Industry 5.0. This issue is becoming decisive for advancement in all areas of life, including science. The primary goal of this study is to concisely explain how current Industry 4.0 trends might interact with existing work systems in global value chains to accelerate their operational activity in the context of firms from the Visegrad Four (V4) nations. Through an examination of the digital abilities in these nations, the purpose of the study is also to demonstrate how well citizens, employees, and end users are able to comprehend the problem at hand. The most recent resources for the topics are covered in the first section of the work. The next one uses graphic analysis and mutual comparison methods, generally comparing existing data over time; it is secondary research, and through these methods the Industry 4.0 applications can significantly speed up the work process itself when compared to the traditional lean process, primarily because of its digital structure. It is difficult to predict which of the V4 will be digitally prepared, as the precedent shifts are based on distinct indicators; therefore, it is crucial that all V4 nations expand their digital adaptability dramatically each year, primarily as a result of spending on scientific research, and education that is organised appropriately. The extra value of this effort may be attributed to how lean processes are intertwined with the Industry 4.0 trend’s digital experience, which already includes the Industry 5.0 trend’s artificial intelligence and metaverse, which represent the potential for further research in the future.

Application of numerical and graphical methods of analysis in nonlinear resistive circuits of electronic devices

The article discusses the research issues and methods of analysis of semiconductor circuits used in electronic circuits of contactless switching devices, provides analytical, graphic and numerical methods for the analysis of nonlinear semiconductor resistive circuits. The approximations of the Volt-Ampere characteristics (VACh) of semiconductor elements and the solution of the differential equations of state of electrical circuits by a numerical method using a computer are given. Diode, thyristor semiconductor nonlinear resistive circuits with active and inductive loads are considered. In the analysis of steady-state modes and transient processes, numerical methods for solving differential equations of states by the Euler method were used.

ДИНАМИКА СМЕРТНОСТИ НАСЕЛЕНИЯ ОМСКОЙ ОБЛАСТИ ПО ОСНОВНЫМ КЛАССАМ ПРИЧИН СМЕРТИ ЗА 2014-2021 ГГ.

Significance. Mortality is one the most important statistical indicators characterizing level of sanitation. This demographic indicator is one of the most common in international health statistics. Of particular interest to health authorities are mortality rates from individual causes. Mortality rate from individual causes depends on prevalence of specific nosological forms of diseases and their lethality. The purpose of the study was to analyze rates and dynamics in mortality in the Omsk region by main class of death causes for the period from 2014 to 2021. Material and methods. Statistical processing of the research materials used methods of alternative (intensive indicators) and graphical analysis; indicators of dynamic series were calculated. Results. During the period from 2014 to 2021, the Omsk region registered a 35% increase in the crude death rate. Diseases of the circulatory system remained the leading cause of death in the Omsk region. Mortality from diseases of the nervous system increased 2.6 times. The COVID-19 pandemic is associated with a high mortality in the region in 2020, followed by a 3.2-fold increase in 2021, ranking second after diseases of the circulatory system. A decrease in mortality was recorded in the classes "Infectious and parasitic diseases" (by 18.8%), "Neoplasms" (by 7.1%), "Diseases of the respiratory system (by 29.0%), "Diseases of the digestive system" (by 10.4%), and "Accidents, injuries, poisoning" (by 29.1%). Conclusion. Statistically significant positive changes were registered during the analysis of dynamics in mortality due to infectious diseases, neoplasms, respiratory diseases, digestive diseases, and external causes. In the region, mortality due to diseases of the circulatory system was characterized by a stable trend and high rates. Negative trends have been noted in the dynamics in mortality associated with COVID-19, and diseases of the nervous system. A significant increase in mortality due to these causes apparently determines the negative trends in the medical and demographic component of the current development of the Omsk region.

Развитие рынка ипотечного кредитования в Российской Федерации в разрезе федеральных округов

Under modern conditions of our life and economy, mortgage credit is a the key source of financing for the purchase of housing and for many people it is the only affordable one. And mortgage itself is increasing, which is undoubtedly the result of its relative availability compared with a long period of funds accumulation necessary to purchase one’s own real estate. In this regard, the problems of mortgage lending development are of paramount importance. In the article the authors analyzed the situation in the segments of housing mortgage lending market in the Russian Federation on federal districts, on the basis of which rapid growth of mortgage programs implementation was predicted. The purpose of the research is to study the trends in the mortgage lending market in Russia as a whole and, on this basis, to conduct comprehensive analysis of mortgage lending development from the point of view of federal districts and commercial banks operating in them. Methods of comparison, dynamic lines, comparison, trend analysis, graphical and tabular methods of analysis of mortgage lending market data from the point of view of federal districts were used. The results of the study made it possible to conclude that mortgage lending market development from the point of view of federal districts is uneven. The obtained results enabled the authors to identify the leading regions in the development of this market segment, and on this basis to determine the top banks that occupy leading positions in issuing mortgage loans. Having analyzed the competitive environment in housing mortgage lending market, it is defined that only system generating banks dominate in this segment. And this is an indication of high competition for distribution of potential customers. In its turn, it will contribute to further increase of the volume of mortgage loans in federal districts and their concentration in separate commercial banks.

Народные художественные промыслы России и «русский сувенир»

Folk arts and crafts are part of the national heritage of Russia, a recognized contribution of Russia to world culture. The preservation, revival and development of folk arts and crafts always remain a topical topic of scientific research and the practice of developing souvenir products in the modern world. The paper presents the results of research on Russian folk arts and crafts: classification models have been developed including both text and illustrative materials, taking into account the geographical location of the centers of production of traditional crafts and materials used in the production, processing techniques and decoration of products. The study comes up with the results of testing the method of structural and graphic analysis of the folk art products based on the study of historical experience and the current level of souvenir production in Russia and abroad. It involves the design project “Souvenir from Russia”, which includes a series of wooden spoons: “Cyrillic” (based on the font graphics of Cyrillic writing), “Splint” (fragmentation of splint paintings and characters), “Ivanovo calico” (based on the plot ornaments of fabrics), “Khokhloma” (fragmentation of pictorial motifs and Cyrillic fontography).

Research of the spent drying agent parameters in the mine grain dryer

Purpose. Improving the energy efficiency of the technological process of grain drying by reducing emissions of thermal energy with the spent drying agent by regulating the thermodynamic potential of the drying agent stream in the grain stream. Methods. To obtain and process the results, methods of engineering, programming, cybernetics, graphical and regression analysis and synthesis using a calculator and applications Matlab and Speq were used. Results. A set of equipment for monitoring the thermodynamic parameters of the technological process of grain drying was developed, manufactured and implemented at an operating mine grain dryer. The data of primary accounting of the results of experimental studies on the existing shaft grain dryer of heat and humidity indicators of the spent drying agent at different stages of grain drying were obtained. The energy aspects of increasing the efficiency of using the drying agent in the technological process of grain drying are considered. Conclusions 1. Due to the characteristics of primary measuring converters together with the means of display and archiving of indicators, the developed set of equipment for the control of the thermodynamic parameters of the technological process of drying grain is useful tool for the dryer operator, which cares for the quality of the finished product and energy saving of production. 2. The rational adjustment of the thermodynamic parameters of the drying agent stream provides a reduction in the energy consumption for drying about 6 %. 3. The results of the work can be used in further scientific research on the modernization of operated grain dryers and for the design of innovative energy-saving grain drying processes. Keywords: grain, drying agent, enthalpy, drying, automation, energy saving.

Study of the product structure of Ukraine's exports in the conditions of globalization

Introduction. The urgency of studying the product structure of Ukraine's exports in the face of global challenges is determined by the need to bring its export portfolio into compliance with the requirements of the European Union markets. In order to meet the requirements and standards of the EU during global transformations, Ukraine should adhere to strategic tasks, among which the development of the economy, attracting investments and increasing the export potential are of primary importance. Purpose. Studying the commodity structure of Ukraine's exports, its components and principles of formation, as well as finding ways to improve Ukraine's competitiveness in the context of globalization is the main goal of this study. Method (methodology). The methods of analysis, synthesis, comparison, substantiation, statistical analysis, abstract-logical, graphical and tabular analysis were used in the process of work. Results. Modern concepts of the transformation of the commodity structure of countries' exports and the experience of their implementation have been studied and analyzed. It was found that the concept of "commodity structure of export" is connected with the concepts of "export potential", "trade balance", "competitiveness" and "economic complexity", the last of which means a high variety and differentiation of production, which is reflected in a wide range and high the quality of manufactured goods. The commodity structure of Ukraine's exports was analyzed, where the main groups of goods are agricultural products, machinery and equipment, chemical industry, metallurgy and metal products, energy products and IT services. 4 main ways of transforming Ukraine's export portfolio in order to increase its competitiveness are proposed: diversification of the export portfolio, improvement of product quality and competitiveness, development of new export directions in the EU markets, and introduction of environmental standards. It is also necessary to implement economic reforms, stimulate the investment climate, support entrepreneurship and innovation, which are important components of strategic plans for exports.

Employee recruitment technologies as a human capital management tool

Introduction. Taking into account the need of companies to increase their efficiency and competitiveness, the study of modern technologies of recruiting employees acquires significant relevance. Recruiting has become more popular with the advent of new digital technologies and applications that have made it more complex through the use of specialized tools and modern approaches. The quality of personnel selection determines the future effective economic activity of the company and lays the foundation for its development. Purpose. Study of employee recruiting technologies, their comparison, determination of their success and impact on the development of human capital management. Method (methodology). The methods of analysis, synthesis, comparison, substantiation, statistical analysis, abstract-logical, graphical and tabular analysis were used in the process of work. Results. As a result of the research, the work analyzed trends in the level of vacancies in the EU and Ukraine, compared external and internal recruitment technologies, their success and impact on the development of human capital management. It is proposed to consider the recruitment of employees as a tool for the development of the company's human capital management, which, unlike the recruitment of personnel, which is a normal process, performs a strategic function of human resources management, which aims to attract, evaluate and select potential employees in order to achieve the company's business goals. It has been established that the job market in the EU and Ukraine have similar shrinking tendencies, which differ only in the intensity of the processes. Thus, almost half of all vacancies in Ukraine are vacancies in Kyiv, a fifth are vacancies in Lviv and abroad, and foreign vacancies have positive growth dynamics, in contrast to the opposite dynamics in Ukraine. A comparison of external and internal recruitment technologies was made. It is shown that internal recruiting contributes to the development of the company's human capital, because it uses its internal potential and retains talented employees. Among the external recruiting technologies, the most famous are headhunting, outstaffing and outsourcing. Of the listed technologies, only headhunting contributes to the development of personnel management due to the segregation of highly qualified specialists from other companies. Outstaffing and outsourcing have either a neutral or a negative impact on staff development.

Phenotypic variability in the shield morphology of wild- vs. lab-reared eumalacostracan larvae

Morphological identification of planktic crustacean larvae is required in many scientific contexts, such as ecology or taxonomy. Due to a still low availability of genetic sequences for many ingroups of Eumalacostraca, this task is still more feasible by morphological methods. Our understanding of eumalacostracan larval morphology is challenged by phenotypic variability. We investigated four eumalacostracan ingroups: Galatheidae, Hippoidea, Raninidae and Stomatopoda. Representatives of all four groups develop through spine-bearing planktic larval stages. Incorporating dorsal and lateral shield outlines into three-dimensional shape analysis of the shields, we compare specimens from the wild with laboratory-reared specimens. Using graphical and statistical analysis methods, we find that at least the lateral morphology of the shields of Hippoidea and Raninidae seems to be too strongly dependent on phylogeny to show phenotypic variability with our current sample size, but Hippoidea do show phenotypic variability in their dorsal shield morphology. In Galatheidae and Stomatopoda, a clear difference in shield morphology can be found between wild-caught and laboratory-reared specimens. This difference likely represents phenotypic variability. The exact environmental signals causing this phenotypic variability are still unknown, but some candidates are discussed.