The influence of water temperature and pH on the survival of Fasciola hepatica miracidia

Parasitology ◽  
1984 ◽  
Vol 88 (1) ◽  
pp. 97-104 ◽  
Author(s):  
G. Smith ◽  
B. T. Grenfell
Keyword(s):  
Maximum Likelihood Method ◽  
Fasciola Hepatica ◽  
Good Description ◽  
Survival Function ◽  
Experimental Studies ◽  
Likelihood Method ◽  
Confidence Limits ◽  
Mean Values ◽  
Influence Of Water ◽  
The Mean

SUMMARYExperimental studies on the survival of Fasciola hepatica miracidia show no evidence that miracidial mortality varies with the pH of the medium, at least in the range 6·0–8·0. On the other hand, miracidial mortality is shown to vary with both the temperature of the medium and the age of the larvae. The mean expected life-span of the miracidium decreases from about 35 h at 6°C to about 6° h at 25° C. The Gompertz survival function provides a good description of the miracidial survivorship curves over the range of temperatures used, and we describe, a maximum likelihood method of estimating the mean values of the parameters of this function, together with their approximate 95% confidence limits.

scholarly journals Best estimation for the Reliability of 2-parameter Weibull Distribution

2009 ◽  
Vol 6 (4) ◽  
pp. 705-710
Author(s):  
Baghdad Science Journal
Keyword(s):  
Maximum Likelihood ◽  
Weibull Distribution ◽  
Mean Square Error ◽  
Maximum Likelihood Method ◽  
Likelihood Method ◽  
Statistical Criterion ◽  
Mean Square ◽  
Simulation Process ◽  
The Mean ◽  
Two Parameter

This Research Tries To Investigate The Problem Of Estimating The Reliability Of Two Parameter Weibull Distribution,By Using Maximum Likelihood Method, And White Method. The Comparison Is done Through Simulation Process Depending On Three Choices Of Models (?=0.8 , ß=0.9) , (?=1.2 , ß=1.5) and (?=2.5 , ß=2). And Sample Size n=10 , 70, 150 We Use the Statistical Criterion Based On the Mean Square Error (MSE) For Comparison Amongst The Methods.

THE EXCRETION OF HUMAN CHORIONIC GONADOTROPHIN IN NORMAL PREGNANCY. AN IMMUNOLOGICAL INVESTIGATION

1964 ◽  
Vol 30 (1) ◽  
pp. 79-86 ◽  
Author(s):  
AILEEN F. CONNON
Keyword(s):  
Haemagglutination Inhibition ◽  
Normal Pregnancy ◽  
Chorionic Gonadotrophin ◽  
Human Chorionic Gonadotrophin ◽  
Confidence Limits ◽  
Mean Values ◽  
Immunological Method ◽  
Immunological Investigation ◽  
The Mean ◽  
Immunological Assays

SUMMARY The haemagglutination-inhibition test was investigated as an immunological method for the assay of human chorionic gonadotrophin (HCG). The preparation of a potent antiserum to HCG is described. The results of the assay of HCG during normal pregnancy in ten patients are compared with the results of immunological assays from two Swedish laboratories. The mean values and the 95 % confidence limits for the excretion of HCG from the 10th week of normal pregnancy are calculated.

scholarly journals On the Spike Train Variability Characterized by Variance-to-Mean Power Relationship

2015 ◽  
Vol 27 (7) ◽  
pp. 1530-1548 ◽  
Author(s):  
Shinsuke Koyama
Keyword(s):  
Power Function ◽  
Maximum Likelihood Method ◽  
Brain Regions ◽  
Spike Trains ◽  
Likelihood Method ◽  
Power Relationship ◽  
Mean Power ◽  
Wide Range ◽  
The Mean ◽  
Two Parameters

We propose a statistical method for modeling the non-Poisson variability of spike trains observed in a wide range of brain regions. Central to our approach is the assumption that the variance and the mean of interspike intervals are related by a power function characterized by two parameters: the scale factor and exponent. It is shown that this single assumption allows the variability of spike trains to have an arbitrary scale and various dependencies on the firing rate in the spike count statistics, as well as in the interval statistics, depending on the two parameters of the power function. We also propose a statistical model for spike trains that exhibits the variance-to-mean power relationship. Based on this, a maximum likelihood method is developed for inferring the parameters from rate-modulated spike trains. The proposed method is illustrated on simulated and experimental spike trains.

The DASH and the QuickDASH instruments. Normative values in the general population in Norway

2013 ◽  
Vol 39 (2) ◽  
pp. 140-144 ◽  
Author(s):  
T. Aasheim ◽  
V. Finsen
Keyword(s):  
General Population ◽  
Normative Data ◽  
The Elderly ◽  
Population Based ◽  
Normative Values ◽  
Confidence Limits ◽  
Mean Values ◽  
Co Morbidity ◽  
The Mean ◽  
Spearman’S Correlation

We collected population-based normative data for the DASH (disabilities of the arm, shoulder and hand ) and QuickDASH questionnaires in order to determine the co-morbidity to be expected in a group of patients. We also studied the correlation between the two scores. A total of 2000 DASH forms and 800 QuickDASH forms were mailed to 1400 men and 1400 women. They were selected randomly in groups of 200 men and women in each age decade from 20–29 to over 80 years old. A total of 50% of the DASH forms and 56% of the QuickDASH forms were returned ( p < 0.005). The mean DASH scores for women rose with age from 5 among those aged 20–29, to 22 among those aged 70–79 and 36 for those over 80. The corresponding mean values for men were 5, 13 and 22. The mean DASH and QuickDASH scores extracted from the DASH forms were very similar in each age decade. Spearman’s correlation coefficient for the two forms was 0.965 for all 992 forms and 0.930 for the 174 forms with scores of 30 or more. There were, however, wide confidence limits for the agreement between scores in individual patients. The high average scores in the general population, particularly among the elderly, should be borne in mind when evaluating scores among patients. The QuickDASH should be preferred to the full DASH as it gives the same information, but is shorter and completed more often.

scholarly journals ANALISIS MODEL PELUANG BERTAHAN HIDUP (SURVIVAL) DAN APLIKASINYA

2013 ◽  
Vol 12 (2) ◽  
pp. 51
Author(s):  
S. FAJARIYAH ◽  
H. SUMARNO ◽  
N. K. K. ARDANA
Keyword(s):  
Maximum Likelihood ◽  
Weibull Distribution ◽  
Life Table ◽  
Survival Data ◽  
Maximum Likelihood Method ◽  
Survival Function ◽  
Likelihood Method ◽  
Real Distribution ◽  
Life Table Data ◽  
Table Data

Up till now, models of demography mathematics usually use discrete approximation. This research will use continue approximation agree with demography characteristic that always change every times.  The Maximum Likelihood method is chosen by using five distributions. There are two data that use i.e. hypothetic data and life table data of Banten. The result of hypothetic data shows that if we choose real distribution, it will produce the good value of 2 R , whereas with survival data of Banten. The result shows that Weibull distribution is the best from another distributions. Keywords: survival function, maximum likelihood method.

scholarly journals Vulnerability of different classes of low-rise buildings in the
1987 Edgecumbe, New Zealand, earthquake

1997 ◽  
Vol 30 (3) ◽  
pp. 227-241 ◽  
Author(s):  
David J. Dowrick ◽  
David A. Rhoades
Keyword(s):  
New Zealand ◽  
Earthquake Risk ◽  
Confidence Limits ◽  
Damage Cost ◽  
Distribution Fitting ◽  
Mean Values ◽  
Earthquake Resistant Design ◽  
Earthquake Resistant ◽  
The Mean ◽  
Earthquake Risk Assessment

This paper describes an analysis of costs of damage to non-domestic buildings (all tow rise) in the Mw = 6.6 Edgecumbe New Zealand earthquake of 2 March 1987. The damage cost for each building was converted to a damage ratio by dividing it by the replacement value of that building. For the MM7 and MM9 intensity zones, the mean values and statistical distributions of these damage ratios were then found, the lognormal distribution fitting the data well. The data was then divided into subsets according to selected classes of construction, and the vulnerabilities of these classes were measured and compared in terms of their mean damage ratios and the associated 95% confidence limits. The classes of building examined included classifications by era of design, number of storeys, materials of construction, and building use. Valuable insights into earthquake resistant design and earthquake risk assessment parameters were obtained through the differences observed between classes, notably significant reductions in the vulnerability of buildings associated with improved ductility provisions.

scholarly journals A Distribuição Half-Normal Generalizada Discreta: uma distribuição alternativa na análise de dados de contagem

2019 ◽  
Vol 41 ◽  
pp. 27
Author(s):  
Josmar Mazucheli ◽  
Ricardo Puziol De Oliveira ◽  
Jean Carlos Cardoso
Keyword(s):  
Maximum Likelihood Method ◽  
Negative Binomial ◽  
Survival Function ◽  
Discrete Distributions ◽  
Likelihood Method ◽  
Discrete Version ◽  
Data Sets ◽  
Continuous Version ◽  
Binomial Distributions ◽  
General Data

In general, data that are obtained by counting processes, strictly discrete or discretized (from truncations and/or rounding), are analyzed, without exhaustion, by the Geometric, Logarithmic, Poisson and Negative Binomial distributions. In recent years a large number of discrete distributions have been proposed in the literature from the discretization of continuous random variables. Many of the discretization methods preserve one or more characteristics of the continuous version, with the proposal of Nakagawa e Osaki (1975) being the most used. In this paper, from this methodology, which makes use of the survival function, we propose the discrete version of the continuous generalized Half-Normal distribution, introduced in the literature by Cooray e Ananda (2008). Some of its properties are discussed and Monte Carlo simulations evaluate the bias and accuracy of the estimates obtained by the maximum likelihood method and method of moments. Some discrete data sets found in the literature are considered to illustrate the applicability of the proposed distribution.

scholarly journals A new family of polyno-expo-trigonometric distributions with applications

2019 ◽  
Vol 22 (04) ◽  
pp. 1950027
Author(s):  
Farrukh Jamal ◽  
Christophe Chesneau
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Method ◽  
Mean Squared Error ◽  
Real Life ◽  
Likelihood Method ◽  
Lifetime Data ◽  
New Family ◽  
Squared Error ◽  
The Mean ◽  
Special Case

In this paper, a new family of polyno-expo-trigonometric distributions is presented and investigated. A special case using the Weibull distribution, with three parameters, is considered as statistical model for lifetime data. The estimation of the parameters is performed with the maximum likelihood method. A numerical simulation study verifies that the bias and the mean squared error of the maximum likelihood estimators tend to zero as the sample size is increased. Three real life datasets are then analyzed. We show that our model has a good fit in comparison to the other well-known powerful models in the literature.

scholarly journals On the Estimation of Parameter of Weighted Sums of Exponential Distribution

2014 ◽  
Vol 2014 ◽  
pp. 1-3
Author(s):  
N. Abbasi ◽  
A. Namju ◽  
N. Safari
Keyword(s):  
Maximum Likelihood ◽  
Exponential Distribution ◽  
Mean Square Error ◽  
Moment Method ◽  
Maximum Likelihood Method ◽  
Random Variable ◽  
Likelihood Method ◽  
Weighted Sums ◽  
Mean Square ◽  
The Mean

The random variable Zn,α=Y1+2αY2+⋯+nαYn, with α∈ℝ and Y1,Y2,…  being independent exponentially distributed random variables with mean one, is considered. Van Leeuwaarden and Temme (2011) attempted to determine good approximation of the distribution of Zn,α. The main problem is estimating the parameter α that has the main state in applicable research. In this paper we show that estimating the parameter α by using the relation between α and mode is available. The mean square error values are obtained for estimating α by mode, moment method, and maximum likelihood method.

scholarly journals Bayesian Inference on the Generalized Gamma Distribution using Conjugate Priors

2020 ◽  
Vol 28 (2) ◽  
Keyword(s):  
Gamma Distribution ◽  
Maximum Likelihood Method ◽  
Loss Functions ◽  
Likelihood Method ◽  
Generalized Gamma Distribution ◽  
Bayesian Techniques ◽  
Conjugate Priors ◽  
Generalized Gamma ◽  
The Mean ◽  
Least Squares Approach

This paper focuses on the three-parameter generalized gamma distribution and uses Bayesian techniques to estimate its parameters. Many authors con-sidered estimating the parameters of the generalized gamma distribution in a Bayesian framework using Jeffrey’s priors. Others used different loss functions and the least squares approach. This study uses Bayesian techniques to estimate the three-parameter generalized gamma distribution by using conjugate priors. The random Metropolis algorithm is used to simulate the Bayesian estimates of the three parameters. Then these estimates are compared to the maximum like-lihood estimates using the mean error through simulation. It has been shown in this paper that the obtained estimates using this approach is more accurate than the traditional methods of estimation such as the Maximum likelihood method. The same approach is then used to estimate the parameters of mixtures of the generalized gamma parameters using conjugate priors.

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