Jackknife Technique Research Articles

Temperature-dependent age-specific demography of grapevine moth (Lobesia botrana) (Lepidoptera: Tortricidae): jackknife vs. bootstrap techniques

Grapevine moth, Lobesia botrana (Lep. Tortricidae) is a key pest of grape in Iran and other vineyards of the world. In this study, eight constant rearing temperatures (5, 10, 15, 20, 25, 30, 32 and 35 ± 1 °C) along with 60 ± 10% RH and a 16:8 (L:D) h photoperiod were chosen for demographic studies of the grapevine moth. Immature stages were unable to develop when reared at 5 and 35 °C, and the progeny moths were unable to successfully mate at 10, 15 and 32 °C. The overall developmental time of juveniles decreased at 30 °C (from 320.7 ± 3.4 d at 10 °C to 34.2 ± 0.2 d) followed by an increase to 42.5 ± 0.6 d at 32 °C. Based on values of the stable population growth parameters, the temperature of 25 °C was found to be optimal for propagation of grapevine moth. The highest values of the intrinsic rate of increase, gross and net reproductive rates were 0.0719 d −1, 55.5 and 23 females per generation, respectively, at 25 °C. Since jackknife and bootstrap estimates of mean and standard error were mainly similar, both methods may equally be used for uncertainty estimates. Our data suggest that cold storage of grapes will help to control grapevine moth infestations and damage. In many grape growing regions of Iran, the first generation is expected to cause damage. It is expected since our reproductive life table analysis suggests that the hot summer temperatures may restrict pest development during subsequent generations.

Evaluación del crecimiento de la jaiba Callinectes sapidus en la costa de Tamaulipas, México: comparación de tres métodos indirectos

<strong>Abstract: Evaluation of the growth of the blue crab <em>Callinectes sapidus</em> in coastal Tamaulipas, Mexico: comparison of three indirect methods.</strong> The blue crab (<em>Callinectes sapidus</em>) is one of the major fisheries of the state of Tamaulipas, Mexico; both in volume and selling price, such as employment generation, but has little information on its biological characteristics. The aim of this study was to evaluate the growth parameters of the blue crab, establishing the most appropriate method to do it. Length frequency of 17 814 crabs from commercial catch of thirteen locations, including four coastal lagoons, was estimated. The lagoons was El Barril, Madre, Morales and San Andrés., from Tamaulipas, State. Growth parameters were evaluated using indirect methods ELEFAN PROJMAT and SLCA in combination with the jackknife technique to establish the uncertainty of estimates inherent in each method. The growth parameters L ∞ and K were consolidated for purposes of comparison with the growth index phi prime (Φ '). The shell length interval varied between 60 and 205 mm. Estimates by jackknife detected no variability in Φ ' between locations and significant differences between methods. The ranges of values of Φ ' and PROJMAT estimated SLCA (4.70 to 4.71 and 4.66 to 4.70, respectively) were in the range reported in the literature ( 4.201 – 4.798), while lower values ELEFAN contributed significantly ( 3.87 to 4.27 ). The SLCA and PROJMAT methods in combination with the <em>jackknife</em> technique, proved to be the most suitable to estimate the growth parameters of <em>C. sapidus</em>.

Comparison of REML and MINQUE for Estimated Variance Components and Predicted Random Effects

Linear mixed model (LMM) approaches have been widely applied in many areas of research data analysis because they offer great flexibility for different data structures and linear model systems. In this study, emphasis is placed on comparing the properties of two LMM approaches: restricted maximum likelihood (REML) and minimum norm quadratic unbiased estimation (MINQUE) with and without resampling techniques being included. Bias, testing power, Type I error, and computing time were compared between REML and MINQUE approaches with and without Jackknife technique based on 500 simulated data sets. Results showed that MINQUE and REML methods performed equally regarding bias, Type I error, and power. Jackknife-based MINQUE and REML greatly improved power compared to non-Jackknife based linear mixed model approaches. Results also showed that MINQUE is more time-saving compared to REML, especially with the use of resampling techniques and large data set analysis. Results from the actual cotton data analysis were in agreement with our simulated results. Therefore, Jackknife-based MINQUE approaches could be recommended to achieve desirable power with reduced time for a large data analysis and model simulations.

Coupling SWAT and ANN models for enhanced daily streamflow prediction

To improve daily flow prediction in unmonitored watersheds a hybrid model was developed by combining a quasi‐distributed watershed model and artificial neural network (ANN). Daily streamflow data from 29 nearby watersheds in and around the city of Atlanta, Southeastern United States, with leave-one-site-out jackknifing technique were used to build the flow predictive models during warm and cool seasons. Daily streamflow was first simulated with the Soil and Water Assessment Tool (SWAT) and then the SWAT simulated baseflow and stormflow were used as inputs to ANN. Out of the total 29 test watersheds, 62% and 83% of them had Nash–Sutcliffe values above 0.50 during the cool and warm seasons, respectively (considered good or better). As the percent forest cover or the size of test watershed increased, the performances of the models gradually decreased during both warm and cool seasons. This indicates that the developed models work better in urbanized watersheds. In addition, SWAT and SWAT Calibration Uncertainty Procedure (SWAT-CUP) program were run separately for each station to compare the flow prediction accuracy of the hybrid approach to SWAT. Only 31% of the sites during the calibration and 34% of validation runs had ENASH values ⩾0.50. This study showed that coupling ANN with semi-distributed models can lead to improved daily streamflow predictions in ungauged watersheds.

Population and breeding success of Red-headed Vulture <i>Sarcogyps calvus</i> and Egyptian Vulture <i>Neophron percnopterus</i> in central west Nepal

This study on population and breeding success of Red-headed Vulture ( Sarcogyps calvus ) and Egyptian Vulture ( Neophron percnopterus ) was carried out in the middle mountain region of central west Nepal covering Arghakhanchi, Kaski, Palpa, Salyan and Pyuthan districts. A total of 34 days of study were conducted from October 2011 to February 2013 and on each study day observation was conducted between 9h00 to 15h00. We did absolute counts of vulture aggregations in flight in Arghakhanchi, Palpa, Pyuthan and Salyan districts, and on a garbage dump in Kaski district, and used a jack-knife technique to estimate the population size of each vulture species. We estimated a total of 24 Red-headed Vultures and 241 Egyptian Vultures across these five districts. Periodic monitoring of each identified nest was done to determine breeding success and we followed Postupalsky (1974) for the categorisation of nests. Based on active nests as a primary unit, the breeding success of Egyptian Vulture was 62.5% for nine nests identified in breeding year 2012; average nesting cliff/tree height was 27.8 m and that of nests was 14.8 m. In the study we did not find any Red-headed Vulture nests, however fresh juvenile birds were recorded repeatedly in the autumn season. Historical reports indicate Red-headed Vultures and Egyptian Vultures were abundant in Nepal, but have undergone rapid population decline across their ranges in the recent past, which is likely to continue into the foreseeable future. Recent information from India indicates the rate of population decline is 44% per year for Red-headed Vultures and 35% per year for Egyptian Vultures.

Tuning of the hyperparameters for L2-loss SVMs with the RBF kernel by the maximum-margin principle and the jackknife technique

The hyperparameters for support vector machines (SVMs) with L2 soft margins and the radial basis function (RBF) kernel include the parameters for the RBF kernel and the L2-soft-margin parameter C. In this paper, the parameters for the RBF kernel are determined through maximization of a margin-based criterion. This criterion is approximately optimized through solving two easier subproblems: one is related to margin maximization in the input space and the other is related to the determination of the extent of sample spread in the feature space. After that, the L2-soft-margin parameter C is obtained by an analytic formula in terms of a jackknife estimate of the perturbation in the eigenvalues of the kernel matrix. In comparison with SVM model selection based on differentiable bounds, such as radius/margin bounds, experimental results on a number of open data sets show that the proposed approach is efficient and accurate.

Jackknifed whittle estimators

The Whittle estimator (Whittle (1962)) is widely used in time series analysis. Although it is asymptotically Gaussian and efficient, this estimator suf- fers from large bias, especially when the underlying process has nearly unit roots. In this paper, we apply the jackknife technique to the Whittle likelihood in the fre- quency domain, and we derive the asymptotic properties of the jackknifed Whittle estimator. In particular, the second-order bias of the jackknifed estimator is shown to vanish for non-Gaussian stationary processes when the unknown parameter is innovation-free. The effectiveness of the jackknife technique for reducing the bias of the Whittle estimator is demonstrated in numerical studies. Since the Whittle estimator is applicable in many fields, including the natural sciences, signal pro- cessing, and econometrics, the bias-reduced jackknifed Whittle estimator can have widespread use.

Stock assessment of fishery target species in Lake Koka, Ethiopia.

Effective management is essential for small-scale fisheries to continue providing food and livelihoods for households, particularly in developing countries where other options are often limited. Studies on the population dynamics and stock assessment on fishery target species are thus imperative to sustain their fisheries and the benefits for the society. In Lake Koka (Ethiopia), very little is known about the vital population parameters and exploitation status of the fishery target species: tilapia Oreochromis niloticus, common carp Cyprinus carpio and catfish Clarias gariepinus. Our study, therefore, aimed at determining the vital population parameters and assessing the status of these target species in Lake Koka using length frequency data collected quarterly from commercial catches from 2007-2012. A total of 20,097 fish specimens (distributed as 7,933 tilapia, 6,025 catfish and 6,139 common carp) were measured for the analysis. Von Bertalarffy growth parameters and their confidence intervals were determined from modal progression analysis using ELEFAN I and applying the jackknife technique. Mortality parameters were determined from length-converted catch curves and empirical models. The exploitation status of these target species were then assessed by computing exploitation rates (E) from mortality parameters as well as from size indicators i.e., assessing the size distribution of fish catches relative to the size at maturity (Lm), the size that provides maximum cohort biomass (Lopt) and the abundance of mega-spawners. The mean value of growth parameters L∞, K and the growth performance index ø' were 44.5 cm, 0.41/year and 2.90 for O. niloticus, 74.1 cm, 0.28/year and 3.19 for C. carpio and 121.9 cm, 0.16/year and 3.36 for C. gariepinus, respectively. The 95 % confidence intervals of the estimates were also computed. Total mortality (Z) estimates were 1.47, 0.83 and 0.72/year for O. niloticus, C. carpio and C. gariepinus, respectively. Our study suggest that O. niloticus is in a healthy state, while C. gariepinus show signs of growth overfishing (when both exploitation rate (E) and size indicators were considered). In case of C. carpio, the low exploitation rate encountered would point to underfishing, while the size indicators of the catches would suggest that too small fish are harvested leading to growth overfishing. We concluded that fisheries production in Lake Koka could be enhanced by increasing E toward optimum level of exploitation (Eopt) for the underexploited C. carpio and by increasing the size at first capture (Lc) toward the Lopt, range for all target species.

Estimation of the Time Interval between the Administration of Heroin and the Sampling of Blood in Chronic Inhalers.

To develop a model for estimating the time delay between last heroin consumption and blood sampling in chronic drug users. Eleven patients, all heroin inhalers undergoing detoxification, were included in the study. Several plasma samples were collected during the detoxification procedure and analyzed for the heroin metabolites 6-acetylmorphine (6AM), morphine (MOR), morphine-6-glucuronide (M6G) and morphine-3-glucuronide (M3G), according to a UHPLC/MSMS method. The general linear mixed model was applied to time-related concentrations and a pragmatic four-step delay estimation approach was proposed based on the simultaneous presence of metabolites in plasma. Validation of the model was carried out using the jackknife technique on the 11 patients, and on a group of 7 test patients. Quadratic equations were derived for all metabolites except 6AM. The interval delay estimation was 2-4 days when only M3G present in plasma, 1-2 days when M6G and M3G were both present, 0-1 day when MOR, M6G and M3G were present and <2 h for all metabolites present. The 'jackknife' correlation between declared and actual estimated delays was 0.90. The overall precision of the delay estimates was 8-9 h. The delay between last heroin consumption and blood sampling in chronic drug users can be satisfactorily predicted from plasma heroin metabolites.

Rainfall variability drives interannual variation in N2O emissions from a humid, subtropical pasture

Variations in interannual rainfall totals can lead to large uncertainties in annual N2O emission budget estimates from short term field studies. The interannual variation in nitrous oxide (N2O) emissions from a subtropical pasture in Queensland, Australia, was examined using continuous measurements of automated chambers over 2 consecutive years. Nitrous oxide emissions were highest during the summer months and were highly episodic, related more to the size and distribution of rain events than soil water content. Over 48% of the total N2O emitted was lost in just 16% of measurement days.Interannual variation in annual N2O estimates was high, with cumulative emissions increasing with decreasing rainfall. Cumulative emissions averaged 1826.7±199.9gN2O-Nha−1yr−1 over the two year period, though emissions from 2008 (2148±273gN2O-Nha−1yr−1) were 42% higher than 2007 (1504±126gN2O-Nha−1yr−1). This increase in annual emissions coincided with almost half of the summer precipitation from 2007 to 2008. Emissions dynamics were chiefly driven by the distribution and size of rain events which varied on a seasonal and annual basis.Sampling frequency effects on cumulative N2O flux estimation were assessed using a jackknife technique to inform future manual sampling campaigns. Test subsets of the daily measured data were generated for the pasture and two adjacent land-uses (rainforest and lychee orchard) by selecting measured flux values at regular time intervals ranging from 1 to 30days. Errors associated with weekly sampling were up to 34% of the sub-daily mean and were highly biased towards overestimation if strategically sampled following rain events. Sampling time of day also played a critical role. Morning sampling best represented the 24hour mean in the pasture, whereas sampling at noon proved the most accurate in the shaded rainforest and lychee orchard.

Aggregated functional data model for near-infrared spectroscopy calibration and prediction

Calibration and prediction for NIR spectroscopy data are performed based on a functional interpretation of the Beer–Lambert formula. Considering that, for each chemical sample, the resulting spectrum is a continuous curve obtained as the summation of overlapped absorption spectra from each analyte plus a Gaussian error, we assume that each individual spectrum can be expanded as a linear combination of B-splines basis. Calibration is then performed using two procedures for estimating the individual analytes’ curves: basis smoothing and smoothing splines. Prediction is done by minimizing the square error of prediction. To assess the variance of the predicted values, we use a leave-one-out jackknife technique. Departures from the standard error models are discussed through a simulation study, in particular, how correlated errors impact on the calibration step and consequently on the analytes’ concentration prediction. Finally, the performance of our methodology is demonstrated through the analysis of two publicly available datasets.

Life Table and Consumption Capacity of Corn Earworm,Helicoverpa armigera, Fed Asparagus,Asparagus officinalis

The life table and consumption rate of Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) reared on asparagus, Asparagus officinalis L. (Asparagales: Asparagaceae) were studied under laboratory conditions to assess their interaction. Development, survival, fecundity, and consumption data were analyzed by the age-stage, two-sex life table. This study indicated that asparagus is a natural host of H. armigera. However, the poor nutritional content in asparagus foliage and the poor fitness of H. armigera that fed on asparagus indicated that asparagus is a suboptimal host in comparison to hybrid sweet corn. The uncertainty associated with life table parameters was estimated by using jackknife and bootstrap techniques, and the results were compared for statistical inference. The intrinsic rate of increase (r), finite rate of increase (λ), net reproductive rate (R0), and mean generation time (T) were estimated by the jackknife technique to be 0.0780 day-1, 1.0811 day-1, 67.4 offspring, and 54.8 days, respectively, while those estimated by the bootstrap technique were 0.0752 day-1, 1.0781 day-1, 68.0 offspring, and 55.3 days, respectively. The net consumption rate of H. armigera, as estimated by the jackknife and bootstrap technique, was 1183.02 and 1132.9 mg per individual, respectively. The frequency distribution of sample means obtained by the jackknife technique failed the normality test, while the bootstrap results fit the normal distribution well. By contrast, the relationship between the mean fecundity and the net reproductive rate, as estimated by the bootstrap technique, was slightly inconsistent with the relationship found by mathematical proof. The application of the jackknife and bootstrap techniques in estimating population parameters requires further examination.

Life table and consumption capacity of corn earworm, Helicoverpa armigera, fed asparagus, Asparagus officinalis.

The life table and consumption rate of Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) reared on asparagus, Asparagus officinalis L. (Asparagales: Asparagaceae) were studied under laboratory conditions to assess their interaction. Development, survival, fecundity, and consumption data were analyzed by the age-stage, twosex life table. This study indicated that asparagus is a natural host of H. armigera. However, the poor nutritional content in asparagus foliage and the poor fitness of H. armigera that fed on asparagus indicated that asparagus is a suboptimal host in comparison to hybrid sweet corn. The uncertainty associated with life table parameters was estimated by using jackknife and bootstrap techniques, and the results were compared for statistical inference. The intrinsic rate of increase ( r ), finite rate of increase ( λ ), net reproductive rate ( R 0), and mean generation time ( T ) were estimated by the jackknife technique to be 0.0780 day -1 , 1.0811 day -1 , 67.4 offspring, and 54.8 days, respectively, while those estimated by the bootstrap technique were 0.0752 day -1 , 1.0781 day -1 , 68.0 offspring, and 55.3 days, respectively. The net consumption rate of H. armigera , as estimated by the jackknife and bootstrap technique, was 1183.02 and 1132.9 mg per individual, respectively. The frequency distribution of sample means obtained by the jackknife technique failed the normality test, while the bootstrap results fit the normal distribution well. By contrast, the relationship between the mean fecundity and the net reproductive rate, as estimated by the bootstrap technique, was slightly inconsistent with the relationship found by mathematical proof. The application of the jackknife and bootstrap techniques in estimating population parameters requires further examination.

Modified Moment Estimation for a Two Parameter Gamma Distribution

A study of a modification of moment estimation of a two parameter gamma distribution has been carried out. The scale parameter has been estimated using the Modified Moment Estimates (MMEs) and their performance is compared to the Maximum Likelihood Estimates (MLEs). Modified Moment Estimates are easy to compute relative to Maximum Likelihood Estimates. To adjust their bias, the Jackknife technique has been used. The efficiency of these estimators is compared by calculating their respective variances. The R-has been used to carry out the Monte Carlo simulation of data. The results obtained show that the Modified Moment Estimates perform as well as the Maximum Likelihood Estimates when bias as well as variation of data is taken into account.

Comparación de tres métodos indirectos para estimar el crecimiento de la tilapia &lt;i&gt;Oreochromis aureus&lt;/i&gt; (Perciformes: Cichlidae) en un lago tropical de México

A comparative analysis of three length based methods for estimating growth of the tilapia Oreochromis aureus (Perciformes: Cichlidae) in a tropical lake of Mexico. Several methods are now available to estimate fish individual growth based upon the distribution of body lengths in a population. Comparative analyses of length-based methods have been undertaken mainly for marine species; nevertheless, limited information is available for inland species. Tilapia is one of the most important freshwater fisheries and its growth parameters have been estimated by several authors, usually using one length-based method. Thus, the main objectives of this study were: a) to estimate growth parameters of O. aureus from Chapala lake, Mexico, using three length-based methods ELEFAN, PROJMAT and SLCA; b) to quantify the effect of input data variations in growth parameters estimates by the jackknife technique; and c) to compare the new estimates with those previously reported, through the standard growth index phi. We collected and analyzed a total of 1,973 specimens from commercial landings from January to December 2010. The three length-base methods used in the present study resulted in parameter estimates within the range of those reported in other studies. Results derived from jackknife analysis revealed lowest values in the error percentage and coefficient of variation for L infinity when applying ELEFAN, while PROJMAT showed lowest values in the precision estimators for K, which was very similar to ELEFAN. Estimates of the comparative growth index phi were also very similar to those reported for the same species when studied in different reservoirs. Considering our results, we suggest the use of ELEFAN rather than SLCA due to its accuracy to estimate growth parameters for O. aureus.

H-ATLAS: estimating redshifts of Herschel sources from sub-mm fluxes

Upon its completion the Herschel ATLAS (H-ATLAS) will be the largest submillimetre survey to date, detecting close to half-a-million sources. It will only be possible to measure spectroscopic redshifts for a small fraction of these sources. However, if the rest-frame spectral energy distribution (SED) of a typical H-ATLAS source is known, this SED and the observed Herschel fluxes can be used to estimate the redshifts of the H-ATLAS sources without spectroscopic redshifts. In this paper, we use a subset of 40 H-ATLAS sources with previously measured redshifts in the range 0.5<z<4.2 to derive a suitable average template for high redshift H-ATLAS sources. We find that a template with two dust components T_c = 23.9 K, T_h = 46.9 K and ratio of mass of cold dust to mass of warm dust of 30.1) provides a good fit to the rest-frame fluxes of the sources in our calibration sample. We use a jackknife technique to estimate the accuracy of the redshifts estimated with this template, finding a root mean square of Delta z/(1+z) = 0.26. For sources for which there is prior information that they lie at z > 1 we estimate that the rms of Delta z/(1+z) = 0.12. We have used this template to estimate the redshift distribution for the sources detected in the H-ATLAS equatorial fields, finding a bimodal distribution with a mean redshift of 1.2, 1.9 and 2.5 for 250, 350 and 500 um selected sources respectively. \end{abstract}

Correction. The Life Table and Parasitism Rate of Diadegma insulare (Hymenoptera: Ichneumonidae) Reared on Larvae of Plutella xylostella (Lepidoptera: Plutellidae), with Special Reference to the Variable Sex Ratio of the Offspring and Comparison of Jackknife and Bootstrap Techniques

Correction. The Life Table and Parasitism Rate of <i>Diadegma insulare</i> (Hymenoptera: Ichneumonidae) Reared on Larvae of <i>Plutella xylostella</i> (Lepidoptera: Plutellidae), with Special Reference to the Variable Sex Ratio of the Offspring and Comparison of Jackknife and Bootstrap Techniques

A note on forecasting euro area inflation: leave- $$h$$ h -out cross validation combination as an alternative to model selection

This paper evaluates the jackknife (leave- $$h$$ -out) technique of averaging individual forecasting models. It offers an initial empirical attempt to apply the leave- $$h$$ -out cross-validation (CV) combination scheme to time series forecasting. The problem of obtaining weights for combining individual autoregressive forecasting models is solved by minimizing the CV criterion (as opposed to the simple (equally weighted) average of the considered benchmark models). The procedure is illustrated on the euro area yearly inflation rate. The recursive pseudo-out-of-sample forecasts are estimated with the forecasting period starting at the beginning of the recent economic crisis (August 2008). The results indicate CV’s dominance with respect to benchmark models for longer forecast horizons (more than 4 months ahead). Moreover, a sensitivity analysis is performed in order to examine whether the obtained results are influenced by the choice of forecast horizon or the out-of-sample cut-off point. In the vast majority of cases, the CV combination superiority is indifferent to the forecast horizon selection. Its dominance is also mostly not influenced by the cut-off point choice.

A limited sampling strategy for tacrolimus in liver transplant patients

To develop limited sampling strategy (LSS) equations to estimate area under the curve (AUC0-12) in Chinese adult transplant patients. 26 adult liver transplant patients were included in this study. The blood samples, collected within 12 hours, were analyzed by microparticle enzyme immunoassay. By multiple stepwise linear regression analysis, LSS equations were identified. The predictive performance of these models was validated by the jackknife technique. As a result, the two sampling time point (trough and 4 hours postdose) model accurately predicted AUC0-12. (R2 = 0.949, ICC = 0.976). The two-point LSS equation (AUC0-12 = 7.26 + (2.17·C0) + (8.30·C4)) can be used as a predictable measure of AUC0-12 of tacrolimus in Chinese liver transplant patients.

The Life Table and Parasitism Rate of Diadegma insulare (Hymenoptera: Ichneumonidae) Reared on Larvae of Plutella xylostella (Lepidoptera: Plutellidae), with Special Reference to the Variable Sex Ratio of the Offspring and Comparison of Jackknife and Bootstrap Techniques

Abstract The life table and parasitism rate of Diadegma insulare (Cresson) (Hymenoptera: Ichneumonidae), a larval parasitoid of the diamondback moth Plutella xylostella (L.) (Lepidoptera: Plutellidae), were studied at 25 ± 1°C, 65 ± 10% RH, and a photoperiod of 16:8 (L: D) h. The data were analyzed based on the age-stage, two-sex life table theory. Because the sex ratio of offspring varies with the age of the female parent, we used only female offspring to calculate the intrinsic rate of increase (r), finite rate of increase (λ), net reproductive rate (R0), and mean generation time (T) by using the jackknife technique, the values of which were 0.18407 d-1, 1.2021 d-1, 17.94 offspring, and 15.69 d, respectively. We also calculated these parameters by using bootstrap technique. They were not significantly different from those estimated by using the jackknife technique. We included both male and female offspring in the calculation of the parasitism rate. The net parasitism rate (C0) was 42.63 aphids. Moreover, population projection showed differences between simulated population based on total offspring and female offspring. Because both the offspring sex ratio and the parasitism rate depend on female age, it is necessary to use the age-stage, two-sex life table for a correct analysis. Frequency of the net reproductive rate estimated by using bootstrap technique fit normal distribution well, whereas frequency data estimated by using jackknife technique failed the normality test. We suggest that the jackknife technique should not be used for the estimation of population parameters.